Methods for characterizing and treating cognitive impairment in aging and disease

ABSTRACT

This invention provides methods for identifying genes associated with cognitive impairment and for identifying compounds useful in the treatment of cognitive impairment. The methods can in particular be used to identify genes associated with, and compounds useful in treating, cognitive impairment in aging.

RELATED APPLICATIONS

This application is a divisional application of U.S. patent application Ser. No. 11/990,049, filed Mar. 16, 2009 (now U.S. Pat. No. 8,510,055), which is a national stage application under 35 U.S.C. §371 of International Application PCT/US2006/030446, filed Aug. 3, 2006, which application claims priority from and benefit of 60/705,642, filed Aug. 3, 2005, 60/705,560, filed Aug. 3, 2005, 60/705,559, filed Aug. 3, 2005, 60/705,702, filed Aug. 3, 2005, 60/705,691, filed Aug. 3, 2005, 60/705,686, filed Aug. 3, 2005, 60/705,700, filed Aug. 3, 2005, 60/705,698, filed Aug. 3, 2005, 60/705,662, filed Aug. 3, 2005, 60/705,697, filed Aug. 3, 2005, 60/705,659, filed Aug. 3, 2005, 60/705,683, filed Aug. 3, 2005, 60/705,699, filed Aug. 3, 2005, 60/705,417, filed Aug. 3, 2005, 60/705,418, filed Aug. 3, 2005, 60/705,511, filed Aug. 3, 2005, 60/705,701, filed Aug. 3, 2005, 60/705,661, filed Aug. 3, 2005, 60/705,594, filed Aug. 3, 2005, 60/705,695, filed Aug. 3, 2005, 60/705,512, filed Aug. 3, 2005, 60/705,416, filed Aug. 3, 2005, 60/705,591, filed Aug. 3, 2005, and 60/705,703, filed Aug. 3, 2005. The disclosure of each of these referenced applications is incorporated by reference herein in its entirety.

BACKGROUND OF THE INVENTION

A major focus of the field of aging and dementia is the investigation of the causes of cognitive impairment. Various conditions, such as dementias (e.g., Alzheimer's Disease, Lewy body dementia, vascular dementia, and HIV associated dementia), neurodegenerative diseases (e.g., Huntington's Disease, Parkinson's Disease, amyotrophic lateral sclerosis), neurological disorders (e.g., schizophrenia, depression), and age-related conditions (e.g., Mild Cognitive Impairment, Age-Related Cognitive Decline), are associated with cognitive impairment. As the understanding of cognitive impairment increases, so does the need to develop sensitive methods to both detect and to treat such impairment.

Accumulating evidence suggests that there is a neurogenetic component to cognitive impairment. For example, changes in the mammalian brain appear to parallel alterations in distinct learning and memory processes. See, e.g., Albert, Philos. Trans. R. Soc. Lond. B. Biol. Sci. 352(1362):1703-09 (1997). In particular, alterations in the hippocampal formation are among the most prominent and consistent features observed in age-related cognitive impairment. Gallagher, Philos. Trans. R. Soc. Lond. B. Biol. Sci. 352(1362):1711-7 (1997). Changes in the aged hippocampus also parallel, to some extent, the hippocampal changes observed in other conditions associated with cognitive impairment, such as Alzheimer's Disease. Whitehouse et al., Science. 215(4537):1237-39 (1982); Bartus et al., Science. 17(4558):408-14 (1982); Rapp and Heindel, Curr. Opin. Neurol. 7(4):294-8 (1994). Thus, the effects of aging on hippocampal function may be related at some level to disease processes in progressive neurodegenerative illnesses.

The mammalian hippocampus is a structure that contains distinct populations of neurons organized into separate anatomical subregions. These subregions include, for example, the dentate gyrus (DG) and the Cornu Ammonis (CA) subfields CA1 and CA3. Each hippocampal subregion is characterized by a unique molecular profile. Lein et al. J Neurosci. 24(15):3879-89 (2004). These different profiles may account for the differential vulnerability of these regions to various mechanisms of cognitive impairment. See, e.g., Small et al. Proc. Natl. Acad. Sci. USA. 101(18):7181-6 (2004).

Considerable research has examined the correlation between changes in cognitive function and neuronal changes in specific hippocampal subregions. This research suggests that the specific nature and extent of hippocampal damage parallels in some cases the degree and type of cognitive impairment. See, Jarrard, Behav. Neural. Biol. 60(1):9-26 (1993). For example, synaptic alterations specific to the CA1 region correlate with age-related impairments in cellular responsiveness to glutamate receptor stimulation. Barnes et al., Hippocampus. 2(4):457-68 (1992). Likewise, individual differences in spatial learning ability correlate with expression levels of NR1, an N-methyl-D-Aspartate (NMDA) receptor subunit, selectively in CA3 neurons. Adams et al., J. Comp. Neurol. 432(2):230-43 (2001). And, levels of synaptic markers in the DG correlate with individual levels of cognitive impairment in spatial learning capacity among aged rats. Smith et al., J. Neurosci. 20(17):6587-93 (2000). These correlations do not, however, establish that the neuronal changes cause the observed functional changes. Just as, importantly, changes in the hippocampus and cognitive function do not occur solely as a result of aging per se. Thus, comparisons based on chronological age alone often fail to capture the hippocampal changes that correlate with individual levels of cognitive impairment.

Although some impairment in both cognitive function and hippocampal integrity may be a normal consequence of healthy aging, a significant population of elderly adults experiences a decline in cognitive ability that exceeds normal development. Thus, the effect of aging itself on cognition, in the absence of dementia or disease, is important for defining the boundary between illness and normal aging.

Heterogeneous patterns of progressive cognitive impairment are characteristic of mammalian test populations, e.g., aged humans and aged laboratory animals. The increasing preponderance of ‘individual differences’ in cognitive impairment has been used to characterize normal mammalian aging itself. Baxter and Gallagher, Neurobiol. Aging. 17(3):491-95 (1996).

There is, therefore, a need to elucidate the molecular basis of and to treat cognitive impairment, both in aging and in disease. There is also a need to understand the neurogenetic components of cognitive impairment and to develop a range of treatment options for individuals with varying levels of impaired cognition.

The examination of changes in expressed gene products in the hippocampus of the mammalian brain, as described in this invention, may serve to elucidate the genetic or molecular basis of cognitive impairment. Moreover, the examination of changes in expressed gene products in the aged hippocampus may serve to elucidate the genetic or molecular basis of cognitive impairment in aging. The identification of genes, or a plurality of genes, that are associated with cognitive impairment, and particularly that are associated with age-related cognitive impairment, would also allow the identification of compounds for treating such impairment.

SUMMARY OF THE INVENTION

This invention provides methods for identifying genes and their expressed gene products, e.g., RNAs, polypeptides, peptides and proteins, associated with cognitive impairment and for identifying compounds useful in the treatment of cognitive impairment. The methods of this invention can, in particular, be used to identify genes and expressed gene products associated with and compounds useful in treating cognitive impairment in aging.

This invention provides a method of identifying a gene or a plurality of genes associated with cognitive impairment by determining the abundance of expressed gene products in one or more of CA1, CA3 and DG hippocampal tissue of mammals in a population of aged mammals with cognitive impairment (aged impaired or “AI”), aged mammals without cognitive impairment (aged unimpaired or “AU”) and young mammals (“Y”), and selecting the genes based on a significant change—increase or decrease—in the relative abundance of the gene's expressed gene product in the AI population relative to the combined AU and Y populations or based on a significant change—increase or decrease—in the relative abundance of the gene's expressed gene product in the AU population relative to the combined AI and Y populations. The AI genes and their expressed gene products may be related to and markers of cognitive impairment and unhealthy aging. Conversely the AU genes and their expressed genes products may be related to and markers of adaptive aging to preserve and protect cognitive function.

One preferred gene in accordance with this invention, the abundance of whose expressed gene product in the AI population relative to the expressed gene product in the combined AU and Y populations is decreased is the GABA-A α5 receptor gene (corresponding to GENBANK® accession number NM_(—)017295), as shown in Example 36 and Table 36 (CA3 AI ANOVA decrease) and its homologues.

This invention provides a method of correlating the changed abundance—increase or decrease—of a selected gene's or its homologue's expressed gene product with the level of cognitive impairment or age-related cognitive impairment in each mammal of the AU and AI populations and selecting one or more genes, the changed abundance—increase or decrease—of whose expressed gene product(s) significantly correlates with the level of cognitive impairment or age-related cognitive impairment in the mammal. Preferably, one gene whose decreased expressed gene product significantly correlates with the level of cognitive impairment is the GABA-A α5 receptor gene (corresponding to GENBANK® accession number NM_(—)017295), as shown in Example 10 and Table 10 (CA3 AI ANOVA negative correlation).

This invention also provides methods for identifying compounds useful for treating cognitive impairment by determining the abundance or function, either in a mammalian cell or in the hippocampus of a mammal, of the expressed gene product of at least one gene, identified by the above methods of the invention, or listed in Tables 1-48, or their homologues, in the presence or absence of a candidate compound and identifying a compound from among the candidate compounds that significantly changes that abundance or alters the function of those genes or expressed gene products in the appropriate direction as defined herein, either in the mammalian cell or in the hippocampus of the mammal, preferably in the CA1, CA3 or DG hippocampal tissue from which the gene was identified, to whom the candidate compound is administered. The same method may also be used for identifying compounds useful in treating age-related cognitive impairment by testing the candidate compounds in aged mammals. Preferably, compounds useful for treating cognitive impairment are (1) the GABA-A α5 receptor agonist QH-ii-066 (1-methyl-7-acetyleno-5-phenyl-1,3-dihydro-benzo[e]-1,4-diazepin-2-one), see, Platt et al., Contribution of _(α1)GABA_(A) and _(α5)GABA_(A) Receptor Subtypes to the Discriminative Stimulus Effects of Ethanol in Squirrel Monkeys, J. Pharmacol. Exp. Ther. 313: 658-667 (2005); (2) 6,6 dimethyl-3-(3-hydroxypropyl)thio-1-(thiazol-2-yl)-6,7-dihydro-2-benzothiophen-4(5H)-one, corresponding to compound number 44 in Chambers et al., Identification of a Novel, Selective GABA_(A) α5 Receptor Inverse Agonist Which Enhances Cognition, J. Med. Chem. 46:2227-2240 (2003); and (3) 8-ethylthio-3-methyl-5-(1-oxidopyridin-2-yl)-3,4-dihydronaphthalen-1(2H)-one, corresponding to compound number 19 in Szekeres et al., 3,4-Dihydronaphthalen-1(2H)-ones: novel ligands for the benzodiazepine site of alpha5-containing GABAA receptors. Bioorg. Med. Chem. Lett. 14:2871-2875 (2004).

This invention provides methods for identifying a compound useful in the treatment of cognitive impairment by determining the cognitive status of a mammal in the presence or absence of a candidate compound believed to change the abundance of the expressed gene product of at least one gene, identified by the method of this invention, or listed in Tables 1-48, or their homologues, or to alter the function of those genes or expressed gene products in the appropriate direction, as defined herein, and identifying a compound from among the candidate compounds that beneficially alters the cognitive status of the mammal. The same method may also be used to identify compounds useful for treating age-related cognitive impairment by testing candidate compounds in aged mammals.

DETAILED DESCRIPTION OF THE INVENTION

Unless otherwise defined herein, scientific and technical terms used in this application shall have the meanings that are commonly understood by those of ordinary skill in the art. Further, unless otherwise required by context, singular terms include pluralities and plural terms include the singular. Generally, nomenclatures used in connection with, and techniques of, cell and tissue culture, molecular biology, cell and cancer biology, neurobiology, neurochemistry, virology, immunology, microbiology, pharmacology, genetics and protein and nucleic acid chemistry, described herein, are those well known and commonly used in the art.

The methods and techniques of the present invention are generally performed, unless otherwise indicated, according to conventional methods well known in the art and as described in various general and more specific references that are cited and discussed throughout the present specification. See, e.g. Ausubel et al., “Current Protocols in Molecular Biology”, Greene Publishing Associates (1992, and Supplements to 2003); Cooper and Hausman, “The Cell—A Molecular Approach, 2nd ed.”, Sinauer Associates, Inc., Sunderland, Mass. (2000); Kandel et al., “Principles of Neural Science”, McGraw-Hill Medical, New York, N.Y. (2000); Motulsky, “Intuitive Biostatistics”, Oxford University Press, Inc. (1995); Lodish et al., “Molecular Cell Biology, 4th ed.”, W. H. Freeman & Co., New York (2000); Griffiths et al., “Introduction to Genetic Analysis, 7th ed.”, W. H. Freeman & Co., N.Y. (1999); Gilbert et al., “Developmental Biology, 6th ed.”, Sinauer Associates, Inc., Sunderland, Mass. (2000); Sambrook et al., “Molecular Cloning: A Laboratory Manual, 2d ed.”, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. (1989).

Chemistry terms used herein are used according to conventional usage in the art, as exemplified by “The McGraw-Hill Dictionary of Chemical Terms”, Parker S., Ed., McGraw-Hill, San Francisco, Calif. (1985).

All of the above, and any other publications, patents and published patent applications, referred to in this application are specifically incorporated by reference herein. In case of conflict, the present specification, including its specific definitions, will control.

The Specific Terms Used in the Methods of this Invention

The following terms, unless otherwise indicated, shall be understood to have the following meanings.

“Abundance” refers to the level of expression, activity or amount of an expressed gene product of a gene or its homologue from another organism. The abundance of an expressed gene product includes, but is not limited to, the level of expression of the function that the gene performs and the way in which it does so, including chemical or structural differences and/or differences in binding or association with other factors. It also includes the amount of the product whatever its source, e.g., expression or direct addition to the tissue, cell or animal. Abundance can be detected by any method useful in quantitatively measuring the expressed gene product. These include, for example, enzymatic assays, binding assays, immunoassays, structural and chemical assays (e.g., which measure modifications such as phosphorylation status, conformational changes).

The methods for measuring the abundance of an expressed gene product according to this invention include, but are not limited to, microarray analysis, macroarray analysis, in situ hybridization histochemistry, fluorescent in situ hybridization (FISH), immunocytochemistry (ICC), immunofluorescence, enzyme linked immunosorbent assay (ELISA), fluorescence polarization immunoassay (FPIA), nephelometric inhibition immunoassay (NIA), immunoprecipitation, quantitative polymerase chain reaction (PCR), RNase protection assay, reverse-transcription PCR, competitive PCR, real-time quantitative PCR (i.e., TaqMan PCR), serial analysis of gene expression (SAGE) analysis, two-dimensional gel electrophoresis, mass spectrometry, MALDI-TOF mass spectrometry, radioimmunoassay (RIA) and blot analysis (e.g. Northern blot, Western blot, protein slot blot, immunoblot, dot blot). If desired, any of the expression and activity assays described above can be used in combination, either sequentially or simultaneously. Such assays can also be partially or completely automated, using methods known in the art.

“Aged” refers to a mammal advanced in years, preferably in or near the latter third of their average lifespan. For example, an aged human would be fifty or more years of age. An aged rat would be fifteen months of age or more.

“Age-related cognitive decline” or “ARCD”, or an equivalent construct such as “age-associated memory impairment”, refers to a diagnosis of mild memory deficit that is not expected to worsen considerably over time. As used herein, ARCD can also be defined as Stage 2 on the Global Deterioration Scale (GDS). The GDS is a seven-point rating system of cognitive and functional capabilities. It is widely used for rating cognitive performance in older adults, with scores ranging from normal aging (Stage 1) to severe dementia (Stage 7). Stage 2 is characterized, for example, by the following clinical characteristics: subjective cognitive complaints in the absence of clinically manifest deficit.

“AI” or “aged impaired” refers to one or more aged mammals with cognitive impairment relative to young mammals of the same species. The preferred species used as models of age impairment in this invention is rats. Most preferably, the rat is from an outbred strain. Aged rats naturally segregate into two populations, with about half of the aged rats being AI and about half being aged unimpaired (AU). To identify these populations, the cognitive ability of young and aged rats is measured. Methods for identifying populations of AI rats are known in the art, e.g., Gallagher and Burwell, Neurobiol. Aging 10:691-708 (1989) and an exemplary method is described in the Example. A number of methods for assessing rat cognitive ability are also known, e.g., the Barnes circular maze, the radial arm maze, the Morris water maze, delayed alternation (delayed nonmatch-to-sample), novel object recognition, conditioned avoidance, and fear conditioning.

“ANOVA” or “analysis of variance” refers to a statistical technique broadly applicable for analyzing data. An ANOVA compares the distribution of two or more populations to determine if one or more of the populations are significantly different from the others. The average variance within each of the populations is factored out from the variance between each of the populations before computing the probability of significant differences between the populations. When an ANOVA tests the difference between the means of two (and not more) populations, it is equivalent to a t-test. As used herein, for example, ANOVA is used to test the hypothesis that the abundance of an expressed gene product of a gene or a plurality of genes is different in mammals with cognitive impairment (e.g., the AI population) relative to mammals without cognitive impairment (e.g., the combined AU and Y populations), by computing the probability that significant differences among populations or treatments are too large to be due to chance.

The statistic calculated by an ANOVA is an F-ratio, which reveals the significance of the hypothesis that Y depends on X. It comprises the ratio of two mean-squares: MS[X]/MS[ε], which is the sum of squared deviations from the mean X or ε divided by the appropriate degrees of freedom. One of skill in the art would use standard tables to determine whether the observed F-ratio indicates a significant relationship. When there are two groups, the F-ratio is equivalent to the t as determined by a t-test. As used herein, when the mean abundance of an expressed gene product of a gene or a plurality of genes is being compared between two groups (e.g., between Aged Impaired and Aged Unimpaired with Young) by ANOVA, the F-ratio would be equivalent to the t test statistic, as determined by a t-test.

A “MAS5” statistical analysis produces absolute and comparison analysis results for microarrays and preferably GeneChip microarrays. It is an algorithm for deriving gene expression scores from microarrays based on present or absent calls, where a percentage of transcripts that are considered significantly hybridized to the chip are considered present. The MAS5 analysis also comprises an algorithm, not used in the present invention, that can deduce present, absent and also marginal calls.

A “gcRMA” statistical analysis is another algorithm for deriving gene expression scores from microarrays and preferably GeneChip microarrays. It is an open-source method that is based on robust averaging techniques and sequence-dependent affinity corrections. The robust averaging employed in gcRMA confers a strong immunity to outliers.

“Appropriate direction” refers to the direction of the change in the abundance of the expressed gene product(s) of at least one gene identified by the methods of this invention or listed in Tables 1-48 or their homologues or the change in the function of the gene or expressed gene product. For genes, whose gene products increase in the AI population relative to the combined AU and Y populations, the “appropriate direction” is a decrease or attenuation of function. For genes, whose gene products decrease in the AI population relative to the combined AU and Y population, the “appropriate direction” is an increase or enhancement in function. For genes, whose gene products increase in the AU population relative to the combined AI and Y populations, the “appropriate direction” is an increase or enhancement of function. And, for genes, whose gene products decrease in the AU population relative to the combined AI and Y populations, the “appropriate direction” is a decrease.

“AU” or “aged unimpaired” refers to one or more aged mammals without cognitive impairment relative to young mammals of the same species. The preferred species used as models of age impairment in this invention is rats. Most preferably, the rat is from an outbred strain. As noted above, aged rats naturally segregate into two populations, with about half of the aged rats being AI and about half being AU. To identify these populations, the cognitive ability of young and aged rats can be measured. Methods for identifying populations of AU rats are known in the art, e.g., Gallagher and Burwell, Neurobiol. Aging 10:691-708 (1989), and an exemplary method is described in the Example. A number of methods for assessing rat cognitive ability are known, e.g., the Barnes circular maze, the radial arm maze, the Morris water maze, delayed alternation (delayed nonmatch-to-sample), novel object recognition, conditioned avoidance, and fear conditioning.

“Beneficially alters” refers to the state of promoting, improving, or preserving cognitive function, or of alleviating or attenuating cognitive decline. A beneficial alteration in accordance with this invention also includes the alleviation or amelioration of one or more manifestations of cognitive impairment, or the delay of onset or slowing of the progression of cognitive impairment. A beneficial alteration of this invention includes, but is not limited to, a change in cognitive function sufficient to result in an improved score in a test of cognitive function; the improvement of cognitive function in a subject with impaired cognitive function so that it more closely resembles the function of a control subject, preferably, e.g., a young subject or an aged unimpaired subject; the improvement over an aged cognitively impaired subject or population; and the preservation of cognitive function over time such that it does not decline or fall below the level observed in the subject upon first presentation or diagnosis.

“Candidate compound” or “compound” means a pharmaceutical, chemical or other composition of matter with known or unknown physiological effects. A compound can be any natural or synthetic agent made up of one or more elements, including, but not limited to, a small molecule, peptide, polypeptide, peptidomimetic, carbohydrate, lipid, protein, glycoprotein, lipoprotein, nucleic acid, and antibody. A compound may or may not have been characterized for its target, or mode of action, in cells or animals prior to its use in the methods of this invention.

As used herein, the compound that is identified and selected from among one or more candidate compounds as being useful in treating cognitive impairment refers to a compound that is capable of altering the abundance—increase or decrease—of the expressed gene product of at least one gene identified in accordance with this invention, one or more genes listed in Tables 1-48, or their homologues in the appropriate direction, as defined herein, i.e., in a manner consistent with the beneficial treatment of cognitive function or that is capable of beneficially altering the cognitive status of a mammal to whom it is administered. Preferably, the compound crosses the blood-brain barrier. More preferably, the compound is orally bioavailable.

“Cognitive function” or “cognitive status” refers to any higher order intellectual brain process or brain state, respectively, involved in learning and memory including, but not limited to, attention, information acquisition, information processing, working memory, short-term memory, long-term memory, anterograde memory, retrograde memory, memory retrieval, discrimination learning, decision-making, inhibitory response control, attentional set-shifting, delayed reinforcement learning, reversal learning, the temporal integration of voluntary behavior, and expressing an interest in one's surroundings and self-care.

“Cognitive impairment” or “CI” or an equivalent construct, such as “impaired cognitive function” or “cognitive decline”, refers to a deficit or reduction in cognitive status or cognitive function, as defined above, compared to that same function in an age-matched control subject or more usually a population. Cognitive impairment may be observed as a consequence of aging, as well as in various diseases and conditions, including but not limited to, Alzheimer's Disease, Lewy body dementia, vascular dementia, HIV associated dementia, Huntington's Disease, Parkinson's Disease, amyotrophic lateral sclerosis, schizophrenia, depression, MCI, and ARCD.

“Expressed gene product” refers to any form of expression of a gene that can be detected and measured, for example, RNA, amino acid, peptide, polypeptide or protein. It also includes the product itself, whether or not it was actually derived from expression in the cell or tissues of an animal.

“Hippocampal-dependent function” refers to a cognitive function, more specifically a learning or memory process, that includes the encoding and acquisition of memories for specific facts and events and episodes of experiences. Hippocampal-dependent function includes the processing of memory representations and the maintenance of memories. Hippocampal-dependent function in mammals includes, for example, spatial memory acquisition, long-term spatial memory, and spatial memory retrieval. A mammal with impaired hippocampal-dependent function may display, e.g., anterograde amnesia for newly acquired facts and events, including maze-specific information in a spatial water maze.

“Hippocampal formation” or “hippocampus” or “hippocampal tissue” refers to the whole or part of the hemispheric structure in the brain folded into the ventromedial surface of the temporal lobe, caudal to the amygdaloid complex. Hippocampal tissue comprises hippocampal cells from, without limitation, the CA1, CA3 and DG subregions. Hippocampal cells include, but are not limited to, pyramidal cells of the CA subregions and granule cells of the DG subregion.

“Homologue” refers to a gene that has the same origin and functions in two or more species. Preferably, a mammal's homologue of a gene, as identified by the method of the invention, refers to the mammal's equivalent of a gene identified in another mammalian species, e.g., the genes encoding human and rat growth hormones.

“Level of cognitive impairment” refers to a measure of the degree of cognitive impairment observed in a mammal. In humans, the level of cognitive impairment may be measured by various neuropsychological tests, alone or in combination, including, but not limited to, the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog); Global Deterioration Scale (GDS); the clinical global impression of change scale (CIBIC-plus scale); the Alzheimer's Disease Cooperative Study Activities of Daily Living Scale (ADCS-ADL); the Mini Mental State Exam (MMSE); the Neuropsychiatric Inventory (NPI); the Clinical Dementia Rating Scale (CDR); the Rey Auditory Verbal Learning Test (AVLT), Logical Memory Subtest of the revised Wechsler Memory Scale (WMS-R); the New York University (NYU) Paragraph Recall Test the Cambridge Neuropsychological Test Automated Battery (CANTAB) or the Sandoz Clinical Assessment-Geriatric (SCAG).

In non-human mammalian models, for example, a rat or non-human primate model, the level of cognitive function may be measured by methods including, but not limited to, using a maze in which subjects use spatial information (e.g., Morris water maze, Barnes circular maze, elevated radial arm maze, elevated plus maze, T-maze and others), recognition tests using odor and novel objects, conditioning tests (e.g., fear conditioning, discrimination tasks, active avoidance, illuminated open-field, two-compartment exploratory test, second and third order conditioning tasks), and tests of higher level executive function (e.g., serial reaction time tests, delayed match and non-match to sample, and stimulus-reward associations including choices involving delayed reinforcement).

In addition, the level of cognitive function may be measured in mammals, including humans, using neuroimaging techniques, e.g., Positron Emission Tomography (PET), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), Single Photon Emission Computed Tomography (SPECT), or any other imaging technique that allows one to measure brain function. The level of cognitive function in aging can be tested by any of the above methods using aged mammals.

“Microarray” or “macroarray” refers to an array (i.e. a matrix) that consist of a surface to which probes (e.g., cDNAs, mRNAs, oligonucleotides, peptides, polypeptides, proteins, antibodies or their equivalents) that correspond or are complementary to in sequence or bind to expressed gene products are bound at known or addressable positions. Each position represents a discrete binding site, e.g., a nucleic acid or nucleic acid analogue, to which a particular expressed gene product can specifically bind. Each array typically, but not necessarily, possesses binding sites for products of most or almost all of the expressed gene products in the mammal's genome. It may also be a representative of such genome. A microarray has a higher density of individual probe species or binding sites per area than a macroarray. A nucleic acid or analogue of a binding site can be, e.g., a synthetic oligomer, a full-length cDNA, a less-than full-length cDNA, an expressed sequence tag (EST) as part of a cDNA molecule, or a gene fragment, e.g., an oligonucleotide corresponding to an overlapping portion of a gene. Preferably, oligonucleotide probes are used. Most preferably, the Affymetrix RAT genome 230-2 array (or an equivalent) is used. The RAT genome 230-2 array contains more than 31,000 probe sets to transcripts from approximately 28,000 genes.

“Mild Cognitive Impairment” or “MCI” refers to a condition characterized by isolated memory impairment accompanied by no other cognitive abnormality and relatively normal functional abilities. One set of criteria for a clinical characterization of MCI specifies the following characteristics: (1) memory complaint (as reported by patient, informant, or physician), (2) normal activities of daily living (ADLs), (3) normal global cognitive function, (4) abnormal memory for age (defined as scoring more than 1.5 standard deviations below the mean for a given age), and (5) absence of indicators of dementia (as defined by DSM-IV guidelines). Petersen et al., Srch. Neurol. 56: 303-308 (1999); Petersen, “Mild cognitive impairment: Aging to Alzheimer's Disease.” Oxford University Press, N.Y. (2003).

Diagnosis of MCI usually entails an objective assessment of cognitive impairment, which can be garnered through the use of well-established neuropsychological tests, including the Mini Mental State Examination (MMSE), the Cambridge Neuropsychological Test Automated Battery (CANTAB) and individual tests such as Rey Auditory Verbal Learning Test (AVLT), Logical Memory Subtest of the revised Wechsler Memory Scale (WMS-R) and the New York University (NYU) Paragraph Recall Test. See Folstein et al., J Psychiatric Res 12: 189-98 (1975); Robbins et al., Dementia 5: 266-81 (1994); Kluger et al., J Geriatr Psychiatry Neurol 12:168-79 (1999).

“Non-human animal model” refers to a non-human mammal or other animal or organism useful for research.

“Non-parametric test” refers to a statistical test that does not rely on parametric assumptions such as normality. A non-parametric test is used in place of a parametric test when some assumptions about the underlying population are uncertain. In the present invention, a non-parametric test is used when the test or control population is sampled from a non-Gaussian distribution or when a gene's expressed gene product is too high or too low in abundance to be accurately determined.

One of skill in the art would appreciate that non-parametric tests rank the outcome variable from low to high and then analyze the ranks. Preferably, the non-parametric test used for comparing populations in accordance with this invention is selected from the group consisting of a Mann-Whitney U test, a Wilcoxon rank-sum test, a Wilcoxon matched pairs signed-rank test, a Mann-Whitney-Wilcoxon test, a Kruskal-Wallis analysis of variance by ranks, a Friedman two way analysis of variance and a Kolmogorov-Smirnov test. Preferably, the non-parametric test used for assessing the linear association (i.e. correlation) between variables is the Spearman rank correlation coefficient.

“Overexpressed”, “overexpression” or “increase” in expression refers to an abundance of an expressed gene product that is higher than the abundance of that same product under other conditions or in other cells or tissues. Overexpression or increased expression may be effected, for example, by one or more structural changes to the gene's encoding nucleic acid or encoded polypeptide sequence (e.g., primary nucleotide or amino acid changes or post-transcriptional modifications such as phosphorylation), altered gene regulation (e.g., in the promoters, regulators, repressors or chromatin structure of the gene), a chemical modification, an altered association with itself or another cellular component, an altered subcellular localization, a modification which causes higher levels of activity through association with other molecules in the cell (e.g., attachment of a targeting domain) and the like.

“Parametric test” refers to a statistical test that requires a parametric assumption, such as normality, i.e., the assumption that the data are sampled from a Gaussian distribution. Preferably, the parametric test, used when comparing levels of expression across populations, in accordance with this invention, is an analysis of variance (ANOVA). Preferably, the parametric test used for assessing the linear association (i.e. correlation) between variables is the Pearson correlation coefficient.

“P value” is the probability associated with an obtained statistic, such as an F-ratio or at statistic (see “ANOVA”, infra). If the p value is less than the significance level, preferably 0.05, then the result constitutes evidence against the null hypothesis, which states that there is no difference among a set of true population means.

“Plurality” refers to two or more.

“Significant” refers to a confidence level for a measurement being real as opposed to being due to chance, for example, as the result of a random sampling error. In accordance with this invention, significant means a confidence or significance level of at least 95%, wherein p<0.05. More preferably, a significance level of 99%, wherein p<0.01.

“Treatment” refers to the use of a compound to beneficially alter cognitive function in the treated mammal. A treatment, as used herein, is administered by providing a mammal with a compound by any appropriate means and in any appropriate formulation and dosing regime.

“Underexpressed”, “underexpression” or “decrease” in expression refers to an abundance of an expressed gene product that is lower than the abundance of the same product under other conditions or in other cells or tissues. Such underexpression or decreased expression may be effected, for example, by one or more structural changes to the gene's encoding nucleic acid or polypeptide sequence (e.g., primary nucleotide or amino acid changes or post-transcriptional modifications such as phosphorylation), altered gene regulation (e.g., in the promoters, regulators, repressors or chromatin structure of the gene), an altered structure (which causes reduced levels of activity), an altered association with itself or another cellular component, an altered subcellular localization, a modification which causes reduced levels of activity through association with other molecules in the cell (e.g., binding proteins which inhibit activity or sequestration) and the like.

“Young” or “Y” refers to one or more adolescent or adult mammals in or near the first third of their average lifespan, at or after the age of sexual maturity and when the hippocampus is fully mature. For example, a young human would be twenty-five years of age or less. A young rat would be ten months of age or less, and preferably at least four months of age.

Description of Various Claims of the Invention

This invention provides methods of identifying a gene or a plurality of genes associated with cognitive impairment in a mammal.

The method comprises providing three populations of mammals—AI, AU and Y—as defined above. Preferably, the mammals used in identifying the genes of this invention are rats and most preferably outbred rat strains.

CA1, CA3 and DG hippocampal tissue is prepared from each member of the three populations using conventional techniques. The abundance of the expressed gene products in each member of these populations is then determined using standard techniques. These techniques include microarray analysis, macroarray analysis, in situ hybridization histochemistry, fluorescent in situ hybridization (FISH), immunocytochemistry (ICC), enzyme linked immunosorbent assay (ELISA), immunoprecipitation, quantitative polymerase chain reaction (PCR), serial analysis of gene expression (SAGE) analysis, radioimmunoassay (RIA) and blot analysis. More preferably, microarray analysis is used.

Genes or a plurality of genes are then selected based on a significant change—decrease or increase—in the gene's expressed gene product (e.g., RNAs, proteins, polypeptides and peptides) in the AI population relative to the combined AU and Y populations or in the AU population relative to the combined AI and Y populations.

The significance of the change in the abundance of the expressed gene product is assessed using conventional statistical tests, including parametric and non-parametric tests. Preferably, the parametric test, ANOVA is used. Among the preferred non-parametric tests useful in this invention are a Mann-Whitney U test, a Wilcoxon rank-sum test, a Wilcoxon matched pairs signed-rank test, a Mann-Whitney-Wilcoxon test, a Kruskal-Wallis analysis of variance by ranks, a Friedman two way analysis of variance, and a Kolmogorov-Smirnov test.

The preferred selected genes or plurality of genes whose expressed gene products have increased abundances in CA1, CA3 or DG tissue are displayed in Tables 1, 3, 6, 7, 25, 27, 30, and 31; 9, 11, 14, 15, 33, 35, 38 and 39; or 17, 19, 22, 23, 41, 43, 46 and 47, respectively. Tables 1, 3, 9, 11, 17, 19, 25, 27, 33, 35, 41 and 43 depict the genes whose expressed gene products are increased in the AI populations relative to the combined AU and Y populations. Tables 6, 7, 14, 15, 22, 23, 30, 31, 38, 39, 46 and 47 depict the genes whose expressed gene products are increased in the AU population relative to the combined AI and Y populations.

The preferred selected genes or plurality of genes whose expressed gene products have decreased abundances in CA1, CA3 or DG tissue are displayed in Tables 2, 4, 5, 8, 26, 28, 29 and 32; 10, 12, 13, 16, 34, 36, 37 and 40; or 18, 20, 21, 24, 42, 44, 45 and 48, respectively. Tables 5, 8, 13, 16, 21, 24, 29, 32, 37, 40, 45 and 48 depict the genes whose expressed gene products are decreased in the AI population relative to the combined AU and Y populations. Tables ______ depict the genes whose expressed gene products are decreased in the AU population relative to the combined AI and Y populations.

In some elements of this invention, the change in the abundance—increase or decrease—of the expressed gene product(s) of the selected gene or plurality of genes is also correlated with the level of cognitive impairment in each member of the AU and AI populations. The increased or decreased abundances of the expressed gene products of the selected genes or plurality of genes positively or negatively, respectively, correlate with the learning index or cognitive impairment of the animals when poorer learners have higher or lower abundances, respectively. Thus, some of the genes in the above Tables, which depict the genes whose expressed gene products are increased in the AI population relative to the combined AU and Y populations or in the AU population relative to the combined AI and Y populations, will positively and negatively correlate, respectively, with cognitive impairment. See, e.g., Tables 1, 6, 9, 14, 17, 22, 25, 30, 33, 38, 41 and 46. Other genes whose expressed gene products are decreased in the AI population relative to the combined AU and Y populations or in the AU population relative to the combined AI and Y populations, will negatively or positively, correlate, respectively, with cognitive impairment. See, e.g., Tables 2, 5, 10, 13, 18, 21, 26, 29, 34, 37, 42 and 45.

A gene or a plurality of genes whose abundances of expressed gene product(s) have a significant positive or negative correlation with the learning index or level of cognitive impairment is then selected. The significance of the correlation is assessed using standard methods, including but not limited to parametric and non-parametric statistical tests. Preferably, the parametric Pearson correlation coefficient or the non-parametric Spearman ranked coefficient is used.

The preferred selected genes or plurality of genes, whose expressed gene products have increased abundances in CA1, CA3 or DG tissue and whose abundances positively or negatively, respectively correlate with the learning scores or cognitive impairment of the AI and AU outbred rat populations, are displayed in Tables 1, 6, 25 and 30; 9, 14, 33, 38; and 17, 22, 41 and 46, respectively.

The preferred selected genes or plurality of genes whose expressed gene products have decreased abundances in CA1, CA3 and DG tissue and whose abundances negatively or positively, respectively correlate with the learning scores or cognitive impairment of the AI and AU outbred rat populations are displayed in Tables 2, 5, 26 and 29; 10, 13, 34 and 37; and 18, 21, 42 and 45, respectively.

The Tables referred to above list the rat genes identified in the preferred claims of this invention by GENBANK® or “UniGene” accession numbers. GENBANK® is the National Institute of Health's genetic sequence database and provides an annotated collection of all publicly available DNA sequences (Nucleic Acids Research 33(Database Issue):D34-D36 (2005)). GENBANK® is part of the International Nucleotide Sequence Database Collaboration, which comprises the DNA DataBank of Japan (DDBJ), the European Molecular

Biology Laboratory (EMBL), and GENBANK® at the National Center for Biotechnology Information (NCBI). The actual rat nucleotide sequence of the accession numbers listed herein may be found by searching the GENBANK® database on the “Entrez Nucleotide” portal of the NCBI website. Each UniGene entry comprises a set of transcript sequences that appear to come from the same transcription locus (gene or expressed pseudogene), together with information on protein similarities, gene expression, cDNA clone reagents, and genomic location, and is also accessible on the NCBI website.

Non-rat mammalian homologues, including human homologues, of the selected genes may be determined in a variety of ways. For example, one method is to access the “HomoloGene” portal of the NCBI website. and enter the GENBANK® or UniGene accession number to obtain a listing of all HomoloGene listings showing the homologues in every identified species in which the gene is conserved, including humans. The link on the desired species will produce the Entrez gene listing, which will have a reference ID for the human sequence of the gene. Alternatively, the human homologue may be identified by directly accessing the above-listed Entrez Gene website and entering the rat GENBANK® accession number. A map viewer of the homologous chromosomes is then accessible via the gene link. The map viewer identifies the human homologues and a click on the gene symbol will access several databases, including the Entrez Gene Sequence viewer (sv), which provides genomic, protein and mRNA sequences; HomoloGene (hm), see above; and Consensus CDS (CODS), another gene identification database that contains several links to protein and sequences.

The genes, identified and selected, by the above methods, and those specific individual genes listed in the Tables above, and their homologues are useful in identifying compounds useful in the treatment of cognitive impairment, and preferably cognitive impairment in aging in accordance with this invention.

One method to identify a compound useful in treating cognitive impairment in mammals, particularly humans, in accordance with this invention, comprises the steps of determining the abundance of an expressed gene product in a mammalian cell of the mammalian cell's homologue(s) of a gene or a plurality of genes identified as described above or listed in Tables 1-48 in the presence or absence of a candidate compound.

The mammalian cells can be any species of cell, e.g., human cells, mouse cells, rat cells, non-human primate cells. The cells can be from any known or established mammalian cell line, such as those available from the American Type Culture Collection (ATCC; Mannassas, Va.), for example, CHO cells, HEK293 cells or COST cells. The cells can be in primary cell culture or from a transformed cell line. The cells may naturally express the gene product (i.e., the gene may be wholly endogenous to the cell or multicellular organism) or the cell may be a recombinant cell or transgenic organism comprising one or more recombinantly expressed gene products.

Preferably, the cells are of human origin and more preferably are selected from the group consisting of neuronal cells and glial cells, including but not limited to, oligodendrocytes, astrocytes, microglia, pyramidal cells, granule cells, motoneurons, and Purkinje cells. Methods for culturing neuronal cells are well known see, e.g., Brewer et al., J. Neuroscience Res. 35:567 (1993) [hippocampal neurons]; Walsh et al., Neuroscience 69:915-29 (1995) [suprachiasmatic neurons]; Zoran et al., Dev Biol. 179:212-22 (1996) [motoneuronal cultures]. Preferably, the neuronal cell is a hippocampal cell or line derived from the hippocampus or a hippocampal region. More preferably, the cell is selected from a CA1, CA3 or DG hippocampal cell.

A number of different screening protocols can be utilized to identify compounds that change the abundance of an expressed gene product of a mammalian cell's homologue(s) of a gene or a plurality of genes identified as described above or individually listed in the above Tables in the mammalian cells. In general terms, the methods include culturing the cells in the presence of individual members of a plurality of candidate compounds to identify a compound that significantly changes—increases or decreases—in the appropriate direction, as defined herein, the abundance of an expressed gene product of a mammalian cell's homologue(s) of a gene or a plurality of genes identified as described above or individually listed in the Tables 1-48.

For example, a compound that decreases the abundance or attenuates the function of an expressed gene product of a gene identified in the methods of this invention or listed in Tables 1, 3, 9, 11, 17, 19, 25, 27, 33, 35, 41 and 43 that was increased in the AI population as compared to the combined AU and Y populations would be useful in treating cognitive impairment. Similarly, a compound that increases the abundance or enhances the function of an expressed gene product of a gene identified in the methods of this invention or listed in Tables 2, 4, 10, 12, 18, 20, 26, 28, 34, 36, 42 and 44 that was decreased in the AI population as compared to the combined AU and Y population would be useful in treating cognitive impairment.

In contrast, a compound that decreases the abundance or attenuates the function of expressed gene products of at least one gene identified in the methods of this invention or listed in Tables 5, 8, 13, 16, 21, 24, 29, 32, 37, 40, 45 and 48 that was decreased in the AU populations as compared to the combined AI and Y populations would be useful in treating cognitive impairment. Similarly, a compound that increases the abundance or enhances the function of one or more expressed gene products of at least one gene identified in the methods of this invention or listed in Tables 6, 7, 14, 15, 22, 23, 30, 31, 38, 39, 46 and 47 that was increased in the AU population as compared to the combined AI and Y populations would be useful in treating cognitive impairment.

One or more compounds from among the candidate compounds are then selected based on the compound's ability to significantly change, in the appropriate direction, as defined herein, the abundance or function of the expressed gene product of a selected gene or plurality of genes in the cell treated with the compound. Preferably, one gene whose decreased abundance of expressed gene product significantly correlates (negatively) with the level of cognitive impairment is the GABA-A α5 receptor gene (corresponding to GENBANK® accession number NM_(—)017295), as shown in Example 10 and Table 10 (CA3 AI ANOVA negative correlation) and its homologues. Preferably, compounds that can significantly increase the abundance or enhance the function of GABA-A α5 protein produced by the gene would be useful for treating cognitive impairment are (1) the GABA-A α5 receptor agonist QH-ii-066 (1-methyl-7-acetyleno-5-phenyl-1,3-dihydro-benzo[e]-1,4-diazepin-2-one), see, Platt et al., Contribution of _(α1)GABA_(A) and _(α5)GABA_(A) Receptor Subtypes to the Discriminative Stimulus Effects of Ethanol in Squirrel Monkeys, J. Pharmacol. Exp. Ther. 313: 658-667 (2005); (2) 6,6 dimethyl-3-(3-hydroxypropyl)thio-1-(thiazol-2-yl)-6,7-dihydro-2-benzothiophen-4(5H)-one, corresponding to compound number 44 in Chambers et al., Identification of a Novel, Selective GABA_(A) α5 Receptor Inverse Agonist Which Enhances Cognition, J. Med. Chem. 46:2227-2240 (2003); and (3) 8-ethylthio-3-methyl-5-(1-oxidopyridin-2-yl)-3,4-dihydronaphthalen-1(2H)-one, corresponding to compound number 19 in Szekeres et al., 3,4-Dihydronaphthalen-1(2H)-ones: novel ligands for the benzodiazepine site of alpha5-containing GABAA receptors. Bioorg. Med. Chem. Lett. 14:2871-2875 (2004).

Another method of identifying compounds useful in treating cognitive impairment assays the candidate compounds in mammals, preferably aged mammals, and more preferably aged mammals with cognitive impairment. In this element, the abundance or function of the expressed gene product of the mammal's homologue of a gene or plurality of genes selected in accordance with this invention or individually listed in the above Tables, is measured in hippocampal tissue, preferably CA1, CA3 or DG tissue of the mammal, to whom the candidate compound has been administered. Those compounds that cause a significant change—increase or decrease—in the appropriate direction, as defined herein, in that abundance or function in mammals treated with the compound are selected.

Compounds are selected that significantly change—increase or decrease—in the appropriate direction, as defined herein, the abundance or function of the expressed gene product of the mammal's homologue of a gene or plurality of genes selected in the method described above or individually listed in the above Tables in an aged mammal with cognitive impairment who has been treated with the compound, relative to a member of the group consisting of an aged mammal without cognitive impairment, a young mammal, an aged cognitively impaired mammal in the absence of the compound, and two or more of them. Preferably, the selected compound does not alter that abundance or function in a young mammal and/or an aged cognitively unimpaired mammal to whom the candidate compound is administered. Also preferably, the selected compound does not significantly alter the cognitive status of a young mammal and/or an aged cognitively unimpaired mammal to whom the candidate compound is administered.

The methods of this invention for identifying compounds useful in the treatment of cognitive impairment, and preferably that due to aging, also include assays based on the cognitive status of a mammal in the presence and absence of the candidate compound.

The cognitive status of a mammal, preferably an aged mammal and most preferably an aged cognitively impaired mammal, and more preferably a rat, is determined in the presence and absence of a candidate compound. The cognitive status of the mammal may be assessed using various functions. Preferably, the functions are hippocampal-dependent functions. More preferably, the functions are spatial memory acquisition, long-term spatial memory, and spatial memory retrieval.

It is preferable that the candidate compound be one that is believed to increase or decrease, in the appropriate direction, as defined herein, the abundance or function of an expressed gene product of the mammal's homologue of a gene or plurality of genes selected in the methods described above or listed in the Tables.

This belief may be based on actual experimental data using other elements of this invention or may be based on information in the scientific literature. A compound that beneficially alters the cognitive status of the treated animal is then selected as being useful in the treatment of cognitive impairment. Preferably, the selected compound beneficially alters the cognitive status in the treated mammal relative to a member of the group consisting of an aged mammal without cognitive impairment, a young mammal, an aged cognitively impaired mammal to whom the compound is not administered and two or more of them. Preferably, the compound does not significantly alter the cognitive status of young mammals or aged unimpaired mammals of the same species who are treated with the compound.

Candidate compounds for use in the methods of the invention include a wide variety of general types of well-known and available compounds including, but not limited to, small organic molecules (e.g., MW<1000, preferably <500); polypeptides; carbohydrates such as oligosaccharides and polysaccharides; polynucleotides; antibodies, lipids or phospholipids; fatty acids; steroids; amino acid analogs, and peptidomimetics. Candidate compounds can be obtained from libraries, such as natural product libraries and combinatorial libraries. A number of different libraries and collections containing large numbers of natural and synthetic compounds are commercially available and one of ordinary skill in the art would be familiar with methods for preparing and obtaining such libraries. Methods of automating assays are also known that permit screening of several thousands of compounds in a short period.

Compounds identified in accordance with the methods of this invention are useful in the treatment of cognitive impairment in mammals, preferably human, and preferably in methods of treating cognitive impairment in aged mammals, preferably humans. The particular compound from among the compounds selected by the methods of this invention to be used can be determined by those skilled in the art, and will depend, for example, on factors such as the severity of the cognitive impairment; the time period over which treatment of the cognitive impairment is desired; whether the compound is administered in a clinical setting or by the individual; or whether an individual suffers from age-related cognitive impairment.

Compounds, selected in accordance with this invention for use in treating cognitive impairment, and particularly that due to aging, or for use in the screening methods of this invention, can be formulated in pharmaceutical compositions in such a manner to ensure proper distribution in vivo. For example, the blood-brain barrier excludes many highly hydrophilic compounds. To ensure that the selected compounds the blood-brain barrier, they can be formulated, for example, in liposomes, or chemically derivatized. A wide variety of carriers can be used to facilitate targeted drug delivery across the blood-brain barrier to brain tissues, preferably the hippocampus, including but not limited to the use of liposomes, nanoparticles, microparticles, microspheres, encapsulated microbubbles or similar structures which envelope biologically or pharmaceutically active agents, carrier molecules including polymers, and protein including hydrophile proteins.

Administration of a selected compound, or candidate compound(s) to be screened can be in a single dose, or in multiple doses. An effective amount of a compound can be determined by those skilled in the art, and can depend on the chemical and biological properties of the compound and the method of contacting the subject. Typically between 0.1 and 1000 mg/kg is administered daily, for one or more days.

Administration of the compound can be carried out using one of a variety of methods known to those of skill in the art. For example, a compound can be administered, intravenously, arterially, intradermally, intramuscularly, intraperitonealy, intravenously, subcutaneously, ocularly, sublingually, orally (by ingestion), intranasally (by inhalation), intraspinally, intracerebrally, and transdermally (by absorbtion, e.g., through a skin duct). A compound can also appropriately be introduced by rechargeable or biodegradable polymeric devices, which provide for the slow release or controlled delivery of drugs.

Appropriate methods of administering a compound to a mammal will also depend, for example, on the age of the mammal, whether the mammal is active or inactive at the time of administering, whether the mammal is cognitively impaired at the time of administering, and the chemical and biological properties of the compound (e.g. solubility, digestibility, bioavailability, stability and toxicity). Preferably, a compound is administered orally, e.g., to a mammal by ingestion, where the compound is dissolved in food and provided to the mammal at mealtime.

Pharmaceutical compositions for oral administration can be formulated using pharmaceutically acceptable carriers well known in the art in dosages suitable for oral administration that enable the compositions to be formulated as, e.g., tablets, pills, dragees, capsules, liquids, gels, syrups, slurries, suspensions, and the like. Other appropriate routes of administration and doses of the compound can be determined by those skilled in the art.

It will be understood that the efficacy and safety of a compound in laboratory mammals can be evaluated before administering the compound to humans. For example, the compound can be tested for its maximal efficacy and any potential side-effects using several different non-human mammals, across a range of doses, in a range of formulations, and at various times of day, such as before or after sleeping, before or after eating, and the like. Preferably, the compound selected by the methods of the invention will cause few or no deleterious or unwanted side effects in any of the test populations. More preferably, the compound will cause few or no deleterious side effects in the mammal whose cognitive status is beneficially altered by the administration of the compound. Most preferably, the compound will cause few or no deleterious side effects in an aged cognitively impaired mammal to which the compound is administered.

Illustrative methods of this invention are described in the following Examples. Methods and materials similar or equivalent to those described can also be used in the practice of the present invention and will be apparent to those of skill in the art. The materials, methods, and examples are thus illustrative only and not intended to be limiting.

EXAMPLES

We performed the following examples using rats of an outbred strain behaviorally characterized as described in more detail below into one of three groups: Y, AU and AI.

Behavioral Characterization of Rats

We performed behavioral tests on 9 young (4-6 months) and 18 aged (25-27 months) pathogen-free male outbred Long-Evans rats with the Morris Water Maze (MWM) protocol. An additional 10 aged rats were tested in the MWM, followed by training and testing in the Radial Arm Maze to assess test-retest reliability for individual differences in cognitive function across the two tasks.

Morris Water Maze Apparatus

In the MWM assay, rats learn and remember the location of an escape platform guided by a configuration of spatial cues surrounding the maze. See, Morris, Learning and Motivation 12:239-260 (1981). The cognitive basis of performance is tested in probe trials using measures of the animal's spatial bias in searching for the location of the escape platform. Aged rats in the study population have no difficulty swimming to a visible platform, but an age-dependent cognitive impairment can be detected when the platform is camouflaged, requiring the use of spatial information.

When reassessed using the MWM in a new spatial environment several weeks after the original characterization, the AI animals are consistently impaired, whereas the AU animals again perform proficiently. Colombo et al., Proc. Natl. Acad. Sci. USA, 94:14195-99 (1997). The difference in cognitive ability in the MWM assessment for AI and AU rats is reliable even over an interval of 3 months. See, Gallagher and Burwell, Neurobiol. Aging 10:691-708 (1989). Further, AI and AU characterization in the MWM differentiates the performance of the same aged subjects in other behavioral tasks that require the same cognitive function, such as the Barnes circular maze, and the radial arm maze (RAM). This naturally occurring impairment in an aged population of rodents indicates that cognitive aging is not inevitable or strictly linked to chronological age, and, importantly, it affords the opportunity to compare the trajectory of changes in the brain that lead to decline or preserved memory.

The MWM apparatus consists of a large, circular pool (diameter 1.83 m; height, 0.58 m) filled with water (27° C.) that has been made opaque through the addition of non-toxic pigment or some other substance. In the typical “hidden platform” version of the task, rats are trained to find a camouflaged white escape platform (height, 34.5 cm) that is positioned in the center of one quadrant of the maze just 1.0 cm below the water surface. This platform can be retracted to the bottom of the tank or raised to its normal position from outside the maze during behavioral testing. The location of this platform remained constant from trial to trial. Because there were no local cues that marked the position of the platform, the rat's ability to locate it efficiently from any starting position at the perimeter of the pool depended on using information surrounding the maze. The maze was surrounded by black curtains with white patterns affixed to provide a configuration of spatial cues.

A second platform (height 37.5 cm) with its surface painted black was elevated 2 cm above the water surface during cue training, the version of the task used to control for factors unrelated to cognition. The behavior of a rat in the pool was recorded by a camera suspended 2.5 m above the center of the pool, connected to a video tracking system (HVS Image Advanced Tracker VP200) and a PC computer running HVS software developed by Richard Baker of HVS Image, Hampton, UK.

Morris Water Maze Procedure

We optimized the MWM protocol for sensitivity to the effects of aging on cognition and for measures of reliable individual differences within the aged population of outbred Long-Evans rats (Gallagher et al., Behav. Neurosci. 107:618-626 (1993)).

Rats received three trials per day for 8 consecutive days, using a 60 second inter-trial interval. On each training trial, the rat was released in the maze from one of four equally spaced starting positions around the perimeter of the pool. The starting position varied from trial to trial, thus preventing the use of a response strategy (e.g. always turning left from the start location to locate the escape platform). If a rat did not locate the escape platform within 90 sec on any trial, the experimenter guided the rat to the platform, where it remained for 30 sec. Every sixth trial consisted of a probe trial to assess the development of spatial bias in the maze. During these trials, the rat swam with the platform retracted to the bottom of the pool for 30 sec, at which time the platform was raised to its normal position for completion of an escape trial. At the completion of the protocol using the hidden platform, rats were assessed for cue learning using the visible platform. The location of this platform varied from trial to trial in a single session of 6 training trials.

We used the proximity of the animal's position with respect to the goal for analysis of training trial and probe trial performance. The proximity measure was obtained by sampling the position of the animal in the maze (10×/sec) to provide a record of distance from the escape platform in 1 sec averages. For both probe trials and training trials, a correction procedure was implemented so that trial performance was relatively unbiased by differences in distance to the goal from the various start locations at the perimeter of the pool. In making this correction the average swimming speed was calculated for each trial (path length/latency). Then, the amount of time required to swim to the goal at that speed from the start location used in the trial was removed from the record prior to computing trial performance, i.e. cumulative distance on training trials and average distance from the goal on probe trials. Thus, scores obtained using the proximity measure are designed to reflect search error, representing deviations from an optimal search, i.e. direct path to the goal and search in the immediate vicinity of that location during probe trials.

Morris Water Maze Analysis

Computer records of video-tracking were compiled to provide data on each rat's performance in the maze. Measures on training trials and probe trials were analyzed by ANOVA.

Morris Water Maze Data Results

The performance during training with the hidden, camouflaged platform differed between the groups of young and aged rats [F(1.23)=12.69, p<0.002]. No difference between the groups occurred for the cue training trials with a visible platform. Latencies to escape during cue training averaged 9.36 seconds for young and 10.60 seconds for the aged rats.

The average proximity measure on interpolated probe trials was used to calculate a spatial learning index for each individual subject as described in detail in Gallagher et al., Behav. Neurosci. 107:618-626 (1993). When a rat rapidly learned to search for the platform close to its position, its spatial learning index is low. Overall, aged rats differed from young [F(1.23)=15.18, p<0.001]. Aged rats were classified as either AU or AI relative to the learning index profile of the young study population. Aged rats that fall within the normative range of young rats (index scores <241) were designated AU. The remaining aged subjects that have index scores outside the range of young performance were designated AI.

Radial Arm Maze Apparatus

Each arm (7×75 cm) of the elevated eight arm radial arm maze (RAM) projected from each facet of an octagonal center platform (30 cm diameter, 51.5 cm height). Clear side walls on the arms were 10 cm high and were angled at 65° to form a trough. A food well (4 cm diameter, 2 cm deep) was located at the distal end of each arm. Blocks constructed of Plexiglas (30 cm H×12 cm W) could be positioned to block entry to any arm. Numerous extra maze cues were provided in the room surrounding the apparatus and overhead fixtures provided lighting.

Radial Arm Maze Procedures

Rats were first habituated to the maze for an 8 min session on four consecutive days. In each of these sessions food rewards were scattered on the RAM, initially on the center platform and arms and then progressively confined to the arms. After this habituation phase, a standard training protocol was used in which a food pellet was located at the end of each arm. Rats received one trial each day for 18 days; each daily trial terminated when all eight food pellets had been obtained or when either 16 choices were made or 15 min had elapsed. An error consisted of returning to an arm (all four paws on the arm) from which food had already been obtained.

After completion of this phase, the memory demand of the task was increased by imposing a delay during the trial. At the beginning of each trial three arms were blocked. The identity and configuration of the blocked arms was varied across trials. Rats were allowed to obtain food on the five arms to which access was permitted at the beginning of the trial. The rat was then removed from the maze for 60 seconds, during which time the barriers on the maze were removed, thus allowing access to all eight arms. Rats were then placed back onto the center platform and allowed to obtain the remaining food rewards.

Radial Arm Maze Analysis

A memory error occurred during test trials using a 60 second delay when a rat returned to one of the five arms that were already visited prior to the delay. Each rat's performance was averaged across four consecutive test trials. Parametric statistics (unpaired t-tests) were used to compare performance between young and aged groups. Correlational analysis (Pearson's r) was used to examine the relationship between performance of aged rats (N=10) in the MWM (learning index scores) and RAM (memory errors).

Radial Arm Maze Results

The performance of young adult rats in the delay version of the RAM varies as a function of the delay interval, ranging from 60 seconds to eight hours (Chappell et al. Neuropharmacology 37: 481-488, (1998)). Aged rats previously characterized in the MWM, committed more memory errors after a 60 second delay relative to young rats (p<0.025). On average young rats committed 0.17 errors, whereas aged rats committed an average of 1.52 errors. The ten aged rats, however, exhibited a wide range of performance on the RAM. A significant relationship was found between the initial MWM characterization and memory performance in the RAM (r value=0.82).

Gene Expression Analysis

We then analyzed the gene expression profiles in the CA1, CA3 or DG hippocampal regions. We determined the abundance of a plurality of expressed gene products in CA1, CA3 or DG hippocampal tissue from each mammal of the three populations—AI, AU and Y. We selected those genes, the abundance of whose expressed gene products was significantly increased or decreased in the AI population as compared to the combined Y and AU populations or significantly increased or decreased in the AU population as compared to the combined Y and AI populations. These genes may relate specifically to age-related cognitive impairment.

We selected from the above genes those whose increased or decreased abundance of expressed gene product(s) showed a significant correlation with the level of cognitive impairment in the AU and AI populations.

These analyses are described below.

Preparation of RNA from Behaviorally Characterized Rats

Twenty-four outbred Long-Evans rats, behaviorally characterized as described above, were killed by live decapitation to obtain fresh brain tissue. The brain was removed, the hippocampus dissected and the CA1, CA3 or DG hippocampal region was microdissected from 500 micron sections taken through the transverse axis of the entire hippocampal formation (both left and right hippocampi) of 24 characterized rats. There were 8 animals in each group (AI, AU and Y) and the CA1, CA3 or DG region of each animal was processed independently.

Total RNA was isolated using Trizol reagent (Invitrogen, Carlsbad, Calif.) according to the standard protocol (homogenization in Trizol reagent followed by chloroform extraction and isopropanol precipitation). Total RNA was further purified using the RNeasy mini kit (Qiagen, Valencia, Calif.). cRNA probes were then generated from the RNA samples at The Johns Hopkins Microarray Core Facility, generally according to Affymetrix specifications as detailed herein.

Briefly, 5 micrograms of total RNA were used to synthesize first strand cDNA using oligonucleotide probes with 24 oligo-dT plus T7 promoter as primer (Proligo LLC, Boulder, Calif.), and the SuperScript Choice System (Invitrogen). Following the double stranded cDNA synthesis, the product was purified by phenol-chloroform extraction, and biotinilated anti-sense cRNA was generated through in vitro transcription using the BioArray RNA High Yield Transcript Labeling kit (ENZO Life Sciences Inc., Farmingdale, N.Y.). 15 ug of the biotinilated cRNA was fragmented at 94° C. for 35 min (100 mM Trix-acetate, pH 8.2, 500 mM KOAc, 150 mM MgOAC). 10 ug of total fragmented cRNA was hybridized to the RAT genome 230-2 Affymetrix GeneChip array for 16 hours at 45° C. with constant rotation (60 rpm). The cRNA prepared from the CA1, CA3 or DG regions for each animal were hybridized to an individual microarray.

Affymetrix Fluidics Station 450 was then used to wash and stain the chips, removing the non-hybridized target and incubating with a streptavidin-phycoerythrin conjugate to stain the biotinilated cRNA. The staining was then amplified using goat immunoglobulin-G (IgG) as blocking reagent and biotinilated anti-streptavidin antibody (goat), followed by a second staining step with a streptavidin-phycoerythrin conjugate.

For quality control of the total RNA from the samples, the Agilent Bioanalyzer, Lab on a Chip technology, was used to confirm that all the samples had optimal rRNA ratios (1:2, for 18S and 28S, respectively) and clean run patterns.

For quality control of the hybridization, chip image, and comparison between chips, the following parameters were considered: Scaling factor: related to the overall intensity of the chip, to confirm the similar signal intensity and staining through out the samples; Background: estimation of unspecific or cross-hybridization; Percentage of present calls (for “MAS5” analysis only, see infra, Data Analysis of Microarray): percentage of transcripts that are considered significantly hybridized to the chip (present) by the algorithm; Glyseraldehyde-3-phosphate dehydrogenase (GAPDH) (3′/5′): representation of the RNA integrity by measuring the ratio of 3′ to 5′ regions for the housekeeping gene GAPDH, its presence in the chip and a ratio close to 1 advocates for a good integrity of the target (sample); Spikes (BioB/BioC) to confirm the detection level and sensitivity after hybridization.

Data Analysis of Microarray

Fluorescence was detected using the Affymetrix G3000 GeneArray Scanner and image analysis of each GeneChip was done through the GeneChip Operating System 1.1.1 (GCOS) software from Affymetrix, using the standard default settings. All of the GeneChip arrays use short oligonucleotides to probe for genes in an RNA sample.

For comparison between different chips, global scaling was used, scaling all probe sets to a user defined target intensity (TGT) of 150. Two different methods were used to estimate the relative expression of genes in different RNA samples. Examples 1-24 processed and summarized the probe set data by “MAS5” analysis. Examples 25-48 processed and summarized the probe set data by “gcRMA” analysis.

The first method, the MAS5 statistical method, produces absolute and comparison analysis results for GeneChip expression arrays. Mas5 employs a statistical algorithm that performs a background adjustment by making regional adjustments or “calls”. This process makes expression level calls as to whether a particular probe set is present or absent. (See, Affymetric statistical algorithm description document, available on the Affymetrix website.)

In Examples 1-24, the total number of present calls and scaling factors were similar across all chips (normalization was scaled by a constant). Further analysis for presence/absence and statistical difference was performed on a region by region basis in the following manner. Probe sets were determined to be present in a region if it had a present call in four of eight animals in a single group, as per the standard MAS5 default settings using Affymetrix software.

The second method used to process and summarize the probe set data was “gcRMA” analysis. This statistical method employs background adjustment by estimating a global signal over the entire probe set and making a whole array adjustment, using quantile normalization. GcRMA is an open-source method that is based on robust averaging techniques and sequence-dependent affinity corrections. The robust averaging employed in gcRMA confers a strong immunity to outliers. See, Wu et al. A Model Based Background Adjustement for Oligonucleotide Expression Arrays. Journal of American Statistical Association. 99:909-917 (2004).

In Examples 25-48, gcRMA analysis was used to perform background and normalization processing, which coupled all the genes together, as did the MAS5 analysis in Examples 1-24. Further analysis for statistical difference included performing a background subtraction. Mismatched sequences (11 for each probe set) were ignored and only the perfect match sequences were considered. There was no elimination of genes based on present/absent calls. See, Quin et al., Evaluation of methods for oligonucleotide array data via quantitative real-time PCR. BMC Bioinformatics, 7:23 (2006).

For Examples 25-48, probe sets were annotated using the most recent Affymetrix annotation of April 2006 and all probe sets representing a specific gene were identified. For Examples 1-24, probe sets were annotated using the Affymetrix annotations of Jun. 20, 2005.

The probe set signal values were then analyzed in the following Examples by various statistical methods to identify those genes or plurality of genes expressed gene products that significantly changed in abundance—increase or decrease—and to identify those genes whose increased or decreased expression product(s) abundance correlated to cognitive impairment.

Example 1

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 1 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 1 CA1 - AI ANOVA POSITIVE CORRELATION GENBANK ® ID UniGene ID BI295776 Rn.110441 AA963364 Rn.11453 AY190520 NM_001002016 NM_001005534 NM_001008374 NM_001008862 NM_001012177 NM_001013112 NM_012543 NM_012577 NM_012650 NM_012918 NM_013001 NM_013157 NM_017068 NM_017223 NM_017347 NM_019212 NM_019289 NM_019305 NM_019359 NM_019362 NM_021657 NM_022244 NM_022261 NM_022617 NM_023981 NM_024138 NM_030863 NM_031037 NM_031147 NM_031818 NM_053418 NM_053485 NM_053525 NM_053536 NM_053669 NM_053774 NM_053896 NM_053910 NM_057103 NM_080887 NM_130413 NM_133621 NM_134390 NM_145674 NM_172038 NM_173325 NM_175582 NM_198738 NM_198759 NM_207602 NM_212528 XM_214769 XM_214968 XM_215095 XM_216004 XM_221231 XM_224538 XM_230616 XM_235566 XM_237000 XM_243637 XM_340967 XM_343773 XM_344524 XM_345140 XM_575962

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 2

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 2 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 2 CA1 - AI ANOVA NEGATIVE CORRELATION GENBANK ® ID UniGene ID BG381750 Rn.101929 NM_001004210 NM_001004279 NM_001004442 NM_001011955 NM_001012035 NM_001013178 NM_001024765 NM_012919 NM_013083 NM_013086 NM_017322 NM_020078 NM_022395 NM_022867 NM_022934 NM_024000 NM_030861 NM_031699 NM_031707 NM_031730 NM_031821 NM_053328 NM_053402 NM_053434 NM_053686 NM_053748 NM_053883 NM_133563 NM_134383 NM_134408 NM_138838 NM_139091 NM_153472 NM_172332 NM_173133 NM_199091 XM_214043 XM_214245 XM_214428 XM_214836 XM_215812 XM_215883 XM_216102 XM_216884 XM_217464 XM_217893 XM_218502 XM_218506 XM_220281 XM_220629 XM_221635 XM_222773 XM_223693 XM_226779 XM_232995 XM_235878 XM_236914 XM_341663 XM_342044 XM_342920 XM_343059 XM_343154 XM_343581

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 3

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 3 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 3 CA1 - AI ANOVA INCREASE GENBANK ® ID UniGene ID AJ249701 Rn.116787 NM_017154 Rn.129174 AW528959 Rn.24948 AF452647 NM_001002835 NM_001004209 NM_001005539 NM_001005565 NM_001007654 NM_001007682 NM_001007749 NM_001009651 NM_001011890 NM_001011934 NM_001011946 NM_001011974 NM_001011993 NM_001012069 NM_001012097 NM_001012141 NM_001012154 NM_001012351 NM_001013086 NM_001013118 NM_001013121 NM_001013179 NM_001013238 NM_001015004 NM_012488 NM_012512 NM_012523 NM_012562 NM_012654 NM_012671 NM_012703 NM_012749 NM_012771 NM_012823 NM_012838 NM_012884 NM_012899 NM_012984 NM_013015 NM_013055 NM_013091 NM_013096 NM_013107 NM_013198 NM_017009 NM_017109 NM_017169 NM_017181 NM_017209 NM_017320 NM_017351 NM_017356 NM_019238 NM_019278 NM_019335 NM_019363 NM_019620 NM_021576 NM_021690 NM_022390 NM_022500 NM_022502 NM_022512 NM_022526 NM_022531 NM_022864 NM_022948 NM_024155 NM_024387 NM_030992 NM_031153 NM_031357 NM_031509 NM_031552 NM_031640 NM_031714 NM_031797 NM_031798 NM_053021 NM_053314 NM_053323 NM_053424 NM_053455 NM_053492 NM_053502 NM_053516 NM_053538 NM_053612 NM_053639 NM_053818 NM_054001 NM_057107 NM_057120 NM_057123 NM_057185 NM_057197 NM_080890 NM_130409 NM_130428 NM_133298 NM_133392 NM_133393 NM_133548 NM_133605 NM_134334 NM_134349 NM_134407 NM_134410 NM_138508 NM_138521 NM_138539 NM_138826 NM_139060 NM_139110 NM_139185 NM_139192 NM_139256 NM_145775 NM_153315 NM_153621 NM_173095 NM_173118 NM_173123 NM_173141 NM_175578 NM_175756 NM_176077 NM_178095 NM_182821 NM_199404 NM_207591 NM_212466 XM_213329 XM_213574 XM_213610 XM_214250 XM_214298 XM_214403 XM_214518 XM_215037 XM_215578 XM_215935 XM_216367 XM_216565 XM_216665 XM_216882 XM_217252 XM_217470 XM_219447 XM_220264 XM_221369 XM_221387 XM_223080 XM_223087 XM_223190 XM_223781 XM_223785 XM_224337 XM_225885 XM_227701 XM_228073 XM_229225 XM_230296 XM_231120 XM_231287 XM_232531 XM_232671 XM_234483 XM_237049 XM_341081 XM_341509 XM_342291 XM_342331 XM_342794 XM_343057 XM_343126 XM_343159 XM_343259 XM_343310 XM_343640 XM_343650 XM_573983 XM_576401 XM_579460 XM_579675

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 4

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 4 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 4 CA1 - AI ANOVA DECREASE GENBANK ® ID UniGene ID AI231320 Rn.122667 BF284573 Rn.15446 BF392810 Rn.48866 NM_001002289 NM_001004133 NM_001004284 NM_001009605 NM_001009953 NM_001011901 NM_001011964 NM_001011998 NM_001012011 NM_001012078 NM_001012144 NM_001012179 NM_001012214 NM_001012473 NM_001013036 NM_001013096 NM_001013244 NM_001013910 NM_001014793 NM_012527 NM_012550 NM_012561 NM_012573 NM_012576 NM_012769 NM_012911 NM_012985 NM_013102 NM_017041 NM_017074 NM_017204 NM_017242 NM_017318 NM_017336 NM_019169 NM_019211 NM_020306 NM_021597 NM_021697 NM_021850 NM_022252 NM_022254 NM_022289 NM_022548 NM_031036 NM_031318 NM_031325 NM_031514 NM_031560 NM_031740 NM_031745 NM_031753 NM_031777 NM_032085 NM_053375 NM_053401 NM_053410 NM_053441 NM_053483 NM_053772 NM_053849 NM_053868 NM_053933 NM_057196 NM_057200 NM_080411 NM_080582 NM_080902 NM_133406 NM_133425 NM_133429 NM_138837 NM_138849 NM_138866 NM_138887 NM_144758 NM_172034 NM_173145 NM_181380 NM_184051 NM_198726 NM_212520 U57097 X53232 XM_213426 XM_213679 XM_213906 XM_213954 XM_214454 XM_214668 XM_215566 XM_216158 XM_216656 XM_217115 XM_218828 XM_219128 XM_221496 XM_221888 XM_221962 XM_222251 XM_222661 XM_222726 XM_224707 XM_224929 XM_225220 XM_226888 XM_230449 XM_232220 XM_236932 XM_239171 XM_239260 XM_341157 XM_341239 XM_341391 XM_341712 XM_341745 XM_342107 XM_342344 XM_342600 XM_342808 XM_343046 XM_343175 XM_343761 XM_344594 XM_345861 XM_345981

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 5

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 5 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 5 CA1 - AU ANOVA POSITIVE CORRELATION GENBANK ® ID UniGene ID AI145040 Rn.36521 NM_001007629 NM_001012028 NM_012546 NM_019152 NM_022177 NM_022286 NM_022858 NM_022946 NM_080692 NM_138515 NM_139260 NM_172041 XM_213564 XM_214003 XM_222245 XM_233462 XM_341100 XM_341558 XM_342548 XM_343468 XM_343764 XM_346061

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 6

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 6 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 6 CA1 - AU ANOVA NEGATIVE CORRELATION GENBANK ® ID NM_001002830 NM_001012034 NM_001012036 NM_012806 NM_017126 NM_019249 NM_019361 NM_021754 NM_031058 NM_031315 NM_032083 NM_053578 NM_080584 NM_175604 NM_182844 NM_199397 NM_199463 XM_214033 XM_215528 XM_218041 XM_218963 XM_221213 XM_225253 XM_226334 XM_228197 XM_237115 XM_341694 XM_342580 XM_343228

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 7

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 7 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 7 CA1 - AU ANOVA INCREASE GENBANK ® ID NM_001004256 NM_001007797 NM_001008317 NM_001008509 NM_001008515 NM_001008556 NM_001008876 NM_001009619 NM_001011953 NM_001011979 NM_001012105 NM_001012131 NM_001013110 NM_001013151 NM_001013201 NM_001013210 NM_001013213 NM_001015003 NM_001015015 NM_012935 NM_012992 NM_013088 NM_013150 NM_016994 NM_017000 NM_017031 NM_017137 NM_017271 NM_017303 NM_017306 NM_017313 NM_019251 NM_019257 NM_020092 NM_021266 NM_022215 NM_022270 NM_022545 NM_022921 NM_024125 NM_031087 NM_031623 NM_031694 NM_032065 NM_053662 NM_053842 NM_053876 NM_053901 NM_057101 NM_130740 NM_131911 NM_133411 NM_134326 NM_134395 NM_138536 NM_139253 NM_145084 NM_145092 NM_153303 NM_153475 NM_175762 NM_175764 NM_199117 NM_199118 NM_212496 NM_213565 U77829 XM_213883 XM_214163 XM_215283 XM_215733 XM_215947 XM_216225 XM_216968 XM_217388 XM_218648 XM_218816 XM_219885 XM_221307 XM_221656 XM_221787 XM_227674 XM_232413 XM_236263 XM_236911 XM_237828 XM_341742 XM_341803 XM_342154 XM_342459 XM_342579 XM_342591 XM_343619 XM_344606 XM_345421 XM_573903 XM_575860 XM_576437

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 8

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 8 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 8 CA1 - AU ANOVA DECREASE GENBANK ® ID UniGene ID AI236198 Rn.95299 NM_001004446 NM_001007150 NM_001008279 NM_001013071 NM_001013122 NM_012545 NM_012648 NM_012762 NM_012784 NM_012808 NM_013197 NM_017061 NM_019159 NM_021671 NM_021703 NM_022250 NM_022609 NM_022676 NM_022853 NM_023972 NM_030988 NM_031018 NM_031654 NM_052983 NM_053428 NM_053788 NM_053797 NM_053811 NM_053859 NM_053893 NM_053996 NM_080394 NM_080580 NM_130430 NM_131906 NM_133313 NM_133400 NM_138854 NM_207592 XM_214963 XM_220884 XM_220982 XM_221273 XM_223768 XM_232640 XM_234901 XM_340775 XM_340999 XM_342134 XM_342863 XM_343559 XM_574284

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 9

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 9 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 9 CA3 - AI ANOVA POSITIVE CORRELATION GENBANK ® ID UniGene ID BF420467 Rn.22102 AF452731 AY190520 NM_001001511 NM_001007146 NM_001007617 NM_001007797 NM_001008289 NM_001008331 NM_001008880 NM_001008893 NM_001009474 NM_001011890 NM_001011893 NM_001011915 NM_001011946 NM_001011991 NM_001012025 NM_001012072 NM_001012075 NM_001012097 NM_001012106 NM_001012123 NM_001012162 NM_001012203 NM_001012215 NM_001013112 NM_001013121 NM_001013130 NM_001013192 NM_001013218 NM_001017386 NM_012502 NM_012519 NM_012577 NM_012618 NM_012671 NM_012720 NM_012778 NM_012781 NM_012804 NM_012809 NM_012825 NM_012925 NM_012999 NM_013005 NM_013045 NM_013060 NM_013096 NM_013137 NM_013199 NM_017012 NM_017015 NM_017026 NM_017031 NM_017041 NM_017068 NM_017073 NM_017175 NM_017181 NM_017197 NM_017206 NM_017214 NM_017223 NM_017239 NM_017248 NM_017261 NM_017274 NM_017307 NM_017329 NM_017333 NM_017354 NM_017357 NM_019161 NM_019185 NM_019249 NM_019256 NM_019288 NM_019312 NM_019341 NM_019358 NM_020098 NM_021595 NM_021682 NM_021769 NM_021868 NM_022178 NM_022207 NM_022285 NM_022861 NM_024161 NM_024364 NM_030832 NM_031006 NM_031022 NM_031034 NM_031049 NM_031092 NM_031093 NM_031140 NM_031357 NM_031521 NM_031576 NM_031587 NM_031613 NM_031755 NM_031798 NM_031841 NM_032062 NM_032066 NM_032617 NM_052807 NM_053314 NM_053328 NM_053416 NM_053467 NM_053492 NM_053536 NM_053615 NM_053639 NM_053643 NM_053681 NM_053741 NM_053766 NM_053799 NM_053814 NM_053824 NM_053936 NM_057137 NM_057138 NM_057148 NM_057197 NM_057200 NM_130403 NM_133560 NM_133602 NM_133605 NM_134351 NM_138832 NM_138905 NM_138914 NM_139038 NM_139103 NM_145081 NM_145094 NM_147136 NM_147210 NM_152847 NM_153470 NM_172030 NM_172033 NM_173120 NM_175578 NM_175582 NM_175595 NM_175838 NM_177928 NM_178095 NM_199119 NM_199253 NM_212529 NM_213629 XM_213779 XM_213824 XM_213849 XM_213920 XM_214172 XM_214187 XM_214539 XM_214740 XM_214968 XM_215095 XM_215184 XM_215264 XM_215733 XM_215739 XM_216340 XM_216688 XM_216755 XM_217062 XM_217279 XM_217409 XM_217570 XM_218162 XM_218226 XM_218292 XM_218816 XM_219262 XM_219998 XM_220420 XM_220805 XM_220986 XM_222745 XM_222780 XM_223583 XM_225008 XM_225014 XM_225404 XM_225628 XM_226237 XM_226779 XM_227203 XM_228073 XM_229225 XM_229988 XM_230288 XM_231121 XM_231193 XM_231287 XM_231714 XM_232172 XM_232671 XM_232809 XM_235326 XM_237042 XM_237232 XM_237381 XM_238057 XM_238103 XM_238213 XM_240330 XM_241375 XM_242032 XM_242057 XM_340739 XM_340825 XM_340879 XM_340911 XM_341052 XM_341172 XM_341352 XM_341538 XM_341940 XM_342141 XM_342405 XM_342591 XM_342626 XM_342648 XM_342662 XM_342928 XM_343131 XM_343174 XM_343358 XM_343380 XM_343570 XM_343919 XM_343971 XM_344403 XM_345446 XM_573298 XM_574593 XM_576343 XM_579200 XM_579675

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 10

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 10 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 10 CA3 - AI ANOVA NEGATIVE CORRELATION GENBANK ® ID UniGene ID BG379941 Rn.102180 BM389079 Rn.21816 AI228348 Rn.24317 AY325138 NM_001004133 NM_001004210 NM_001004235 NM_001004442 NM_001005564 NM_001005884 NM_001006972 NM_001007150 NM_001007656 NM_001009605 NM_001009679 NM_001011901 NM_001011923 NM_001011955 NM_001011978 NM_001011996 NM_001012012 NM_001012035 NM_001012103 NM_001012144 NM_001012170 NM_001013087 NM_001013170 NM_001014785 NM_012600 NM_012664 NM_012670 NM_012784 NM_012869 NM_013067 NM_013083 NM_013090 NM_013174 NM_013192 NM_013219 NM_017010 NM_017011 NM_017051 NM_017135 NM_017294 NM_017295 NM_019133 NM_019166 NM_019226 NM_019368 NM_021688 NM_021842 NM_021850 NM_022188 NM_022249 NM_022264 NM_022399 NM_022511 NM_022688 NM_022860 NM_022867 NM_022934 NM_023957 NM_023979 NM_024139 NM_024403 NM_030830 NM_030841 NM_030869 NM_031030 NM_031070 NM_031104 NM_031119 NM_031134 NM_031569 NM_031641 NM_031642 NM_031662 NM_031693 NM_031715 NM_031763 NM_031840 NM_033349 NM_053291 NM_053301 NM_053316 NM_053404 NM_053490 NM_053556 NM_053585 NM_053607 NM_053660 NM_053682 NM_053693 NM_053795 NM_053801 NM_053849 NM_053876 NM_053883 NM_053928 NM_053961 NM_057098 NM_057099 NM_057190 NM_130779 NM_133394 NM_133562 NM_133609 NM_134346 NM_138548 NM_138866 NM_138899 NM_138910 NM_138911 NM_139325 NM_145098 NM_145677 NM_153730 NM_172008 NM_172039 NM_172062 NM_172074 NM_173133 NM_173154 NM_173309 NM_181377 NM_181379 NM_198726 NM_199086 NM_199091 NM_199373 NM_212490 XM_213234 XM_213469 XM_213906 XM_214072 XM_214153 XM_214307 XM_214554 XM_214859 XM_215069 XM_215124 XM_215751 XM_215826 XM_215883 XM_215931 XM_216013 XM_216180 XM_216212 XM_216766 XM_216910 XM_217147 XM_217464 XM_217893 XM_218084 XM_218186 XM_218717 XM_220178 XM_220219 XM_220428 XM_220604 XM_220698 XM_221023 XM_221034 XM_221043 XM_221202 XM_221962 XM_222107 XM_223580 XM_223693 XM_223921 XM_223981 XM_224733 XM_226888 XM_227499 XM_230523 XM_230531 XM_231176 XM_231925 XM_232735 XM_233544 XM_235500 XM_238177 XM_238346 XM_239171 XM_239504 XM_340906 XM_340916 XM_341090 XM_341157 XM_341314 XM_341669 XM_341763 XM_342107 XM_342295 XM_342588 XM_342823 XM_342924 XM_342930 XM_343910 XM_344048 XM_347168 XM_574001 XM_576494 XM_577170

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 11

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 11 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 11 CA3 - AI ANOVA INCREASE GENBANK ® ID BI295776 AI178069 AF022087 AF155825 AF187100 M17422 NM_001005539 NM_001005761 NM_001007002 NM_001007005 NM_001007145 NM_001007607 NM_001007628 NM_001007636 NM_001007641 NM_001007744 NM_001008306 NM_001008316 NM_001008356 NM_001008509 NM_001008767 NM_001009623 NM_001011910 NM_001011954 NM_001011959 NM_001011981 NM_001012040 NM_001012163 NM_001012181 NM_001012193 NM_001012217 NM_001012459 NM_001012464 NM_001013058 NM_001013086 NM_001013148 NM_001013173 NM_001013179 NM_001013195 NM_001013200 NM_001014843 NM_001024278 NM_012507 NM_012532 NM_012543 NM_012654 NM_012655 NM_012714 NM_012747 NM_012749 NM_012776 NM_012788 NM_012844 NM_012908 NM_012913 NM_012948 NM_012984 NM_013015 NM_013016 NM_013044 NM_013088 NM_013107 NM_013132 NM_013176 NM_013198 NM_017009 NM_017024 NM_017030 NM_017060 NM_017062 NM_017075 NM_017109 NM_017125 NM_017148 NM_017192 NM_017200 NM_017347 NM_017365 NM_019140 NM_019146 NM_019152 NM_019156 NM_019168 NM_019252 NM_019269 NM_019311 NM_019318 NM_019359 NM_020073 NM_020084 NM_021663 NM_021672 NM_021681 NM_021694 NM_021746 NM_021853 NM_022184 NM_022198 NM_022226 NM_022236 NM_022250 NM_022270 NM_022272 NM_022390 NM_022500 NM_022592 NM_022629 NM_022799 NM_024148 NM_024154 NM_024155 NM_024373 NM_024404 NM_030872 NM_031035 NM_031052 NM_031091 NM_031144 NM_031235 NM_031509 NM_031556 NM_031599 NM_031620 NM_031648 NM_031771 NM_031772 NM_031797 NM_031818 NM_031837 NM_031970 NM_032083 NM_053021 NM_053323 NM_053349 NM_053418 NM_053534 NM_053538 NM_053576 NM_053749 NM_053763 NM_053794 NM_053901 NM_053917 NM_053926 NM_053985 NM_053986 NM_053994 NM_054001 NM_057139 NM_057187 NM_058210 NM_058211 NM_130420 NM_131911 NM_133298 NM_133300 NM_133303 NM_133307 NM_133318 NM_133383 NM_133398 NM_133418 NM_133534 NM_133571 NM_133615 NM_134334 NM_134349 NM_134372 NM_134411 NM_138506 NM_138521 NM_139115 NM_145092 NM_145678 NM_145777 NM_147206 NM_147207 NM_152790 NM_153298 NM_172029 NM_172334 NM_173118 NM_173153 NM_173328 NM_175764 NM_181363 NM_181388 NM_181639 NM_182737 NM_199093 NM_199270 NM_199390 NM_199401 NM_203335 NM_207609 NM_212508 NM_212523 NM_213628 XM_213270 XM_213329 XM_213421 XM_213484 XM_213684 XM_213688 XM_214035 XM_214403 XM_214480 XM_214967 XM_214979 XM_215080 XM_215361 XM_215576 XM_215607 XM_215889 XM_215924 XM_216004 XM_216188 XM_216386 XM_216565 XM_217197 XM_217239 XM_217651 XM_218195 XM_218337 XM_218523 XM_218617 XM_218939 XM_218977 XM_219785 XM_219885 XM_219948 XM_220357 XM_221497 XM_223190 XM_223535 XM_223781 XM_223786 XM_224337 XM_224944 XM_225147 XM_225160 XM_227217 XM_227444 XM_228164 XM_230284 XM_231620 XM_231749 XM_232194 XM_232343 XM_232354 XM_232364 XM_232732 XM_233141 XM_233403 XM_235057 XM_235558 XM_235566 XM_236020 XM_236227 XM_237371 XM_237415 XM_237754 XM_237907 XM_240311 XM_242062 XM_242644 XM_341494 XM_341495 XM_341548 XM_341578 XM_341584 XM_341605 XM_341957 XM_342007 XM_342291 XM_342317 XM_342545 XM_342653 XM_343055 XM_343117 XM_343205 XM_343259 XM_343274 XM_343332 XM_343395 XM_343468 XM_343552 XM_343773 XM_343975 XM_343986 XM_344112 XM_344409 XM_344785 XM_345825 XM_346854 XM_573810 XM_574618 XM_575585 XM_576312 XM_576519 UniGene ID Rn.110441 Rn.129720

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 12

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 12 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 12 CA3 - AI ANOVA DECREASE GENBANK ® ID BI294968 BF284573 AW142828 L13193 BG663483 AF452727 AY316590 NM_001000716 NM_001004072 NM_001004078 NM_001004132 NM_001004233 NM_001005547 NM_001005554 NM_001005905 NM_001005908 NM_001006970 NM_001006997 NM_001007020 NM_001007608 NM_001007626 NM_001007714 NM_001007728 NM_001007742 NM_001008301 NM_001008323 NM_001008338 NM_001008339 NM_001008520 NM_001008558 NM_001008562 NM_001008766 NM_001008888 NM_001009180 NM_001009258 NM_001009424 NM_001009666 NM_001009677 NM_001009688 NM_001009967 NM_001010965 NM_001011969 NM_001011998 NM_001012060 NM_001012066 NM_001012078 NM_001012119 NM_001012187 NM_001012191 NM_001012468 NM_001012473 NM_001013034 NM_001013059 NM_001013153 NM_001013156 NM_001013178 NM_001013189 NM_001013207 NM_001013235 NM_001014792 NM_001014793 NM_001015003 NM_001017374 NM_001024765 NM_012500 NM_012517 NM_012526 NM_012583 NM_012598 NM_012647 NM_012663 NM_012734 NM_012736 NM_012757 NM_012839 NM_012892 NM_012923 NM_012932 NM_012952 NM_012953 NM_012956 NM_012960 NM_012963 NM_012985 NM_013002 NM_013011 NM_013019 NM_013038 NM_013048 NM_013081 NM_013102 NM_013111 NM_013127 NM_013134 NM_013177 NM_013214 NM_013223 NM_017025 NM_017029 NM_017039 NM_017040 NM_017042 NM_017102 NM_017107 NM_017136 NM_017195 NM_017232 NM_017243 NM_017246 NM_017268 NM_017270 NM_017282 NM_017318 NM_017340 NM_017343 NM_017359 NM_017364 NM_019124 NM_019131 NM_019169 NM_019196 NM_019264 NM_019277 NM_019302 NM_019304 NM_019356 NM_021655 NM_021697 NM_021758 NM_021852 NM_022008 NM_022209 NM_022262 NM_022387 NM_022498 NM_022542 NM_022585 NM_022609 NM_022674 NM_022700 NM_022865 NM_022869 NM_022939 NM_023093 NM_023950 NM_023971 NM_023975 NM_024125 NM_024152 NM_024156 NM_024378 NM_024484 NM_024486 NM_030835 NM_030856 NM_031064 NM_031138 NM_031146 NM_031151 NM_031152 NM_031237 NM_031606 NM_031639 NM_031643 NM_031655 NM_031718 NM_031720 NM_031735 NM_031742 NM_031745 NM_031757 NM_031783 NM_031785 NM_031802 NM_031811 NM_031824 NM_031987 NM_032057 NM_032614 NM_033021 NM_053346 NM_053357 NM_053409 NM_053414 NM_053420 NM_053428 NM_053439 NM_053441 NM_053484 NM_053502 NM_053518 NM_053527 NM_053581 NM_053590 NM_053605 NM_053613 NM_053622 NM_053623 NM_053638 NM_053726 NM_053747 NM_053748 NM_053752 NM_053758 NM_053764 NM_053772 NM_053812 NM_053842 NM_053856 NM_053868 NM_053888 NM_053893 NM_053912 NM_053927 NM_053948 NM_053974 NM_053979 NM_053996 NM_054002 NM_054003 NM_057107 NM_057141 NM_057196 NM_057210 NM_080777 NM_080780 NM_080886 NM_080887 NM_080902 NM_130423 NM_130746 NM_130749 NM_130894 NM_131904 NM_133313 NM_133320 NM_133402 NM_133415 NM_133427 NM_133566 NM_133589 NM_134331 NM_134383 NM_134404 NM_138519 NM_138833 NM_138839 NM_138856 NM_138883 NM_139097 NM_139098 NM_139106 NM_139254 NM_145184 NM_147211 NM_152935 NM_153297 NM_153630 NM_153735 NM_171990 NM_171994 NM_172072 NM_173102 NM_173146 NM_173290 NM_177425 NM_177929 NM_178091 NM_181090 NM_181626 NM_182668 NM_182814 NM_182819 NM_183052 NM_183332 NM_184050 NM_184051 NM_198132 NM_198732 NM_198758 NM_198760 NM_198765 NM_198787 NM_198788 NM_199385 NM_199395 NM_199405 NM_199410 NM_199500 NM_207617 NM_212494 NM_212519 NM_212520 XM_213362 XM_213426 XM_213487 XM_213564 XM_213571 XM_213679 XM_213765 XM_213782 XM_213840 XM_214003 XM_214108 XM_214147 XM_214241 XM_214475 XM_214485 XM_214491 XM_214583 XM_214646 XM_214701 XM_214969 XM_215251 XM_215286 XM_215416 XM_215549 XM_215570 XM_215612 XM_216158 XM_216265 XM_216378 XM_216641 XM_216893 XM_217105 XM_217209 XM_217560 XM_217592 XM_217868 XM_218620 XM_218660 XM_219377 XM_219525 XM_219939 XM_220230 XM_220281 XM_220717 XM_220754 XM_221212 XM_221888 XM_221910 XM_222669 XM_222717 XM_223729 XM_224271 XM_225078 XM_226561 XM_227301 XM_228345 XM_230495 XM_231271 XM_231803 XM_232220 XM_232739 XM_232901 XM_233485 XM_233529 XM_234483 XM_234555 XM_235185 XM_235878 XM_236698 XM_237808 XM_238280 XM_238770 XM_239761 XM_340775 XM_340872 XM_340889 XM_340921 XM_340999 XM_341288 XM_341374 XM_341448 XM_341700 XM_341822 XM_341930 XM_342149 XM_342174 XM_342217 XM_342300 XM_342306 XM_342312 XM_342493 XM_342534 XM_342553 XM_342582 XM_342600 XM_342612 XM_342679 XM_342812 XM_342894 XM_342920 XM_343154 XM_343389 XM_343459 XM_343557 XM_343761 XM_343776 XM_344231 XM_344434 XM_344594 XM_573052 XM_573063 XM_573256 XM_574916 XM_578542 XM_579413 UniGene ID Rn.128732 Rn.15446 Rn.23342 Rn.25029 Rn.92383

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 13

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 13 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 13 CA3 - AU ANOVA POSITIVE CORRELATION GENBANK ® ID BF419095 BF420440 NM_001005889 NM_001009665 NM_001009825 NM_001011974 NM_001012038 NM_001012061 NM_001012150 NM_001012183 NM_001012504 NM_001013128 NM_012504 NM_012518 NM_012527 NM_012574 NM_012633 NM_012836 NM_012920 NM_013029 NM_013065 NM_013066 NM_013126 NM_013135 NM_017065 NM_017066 NM_017211 NM_017213 NM_017242 NM_017262 NM_017290 NM_017304 NM_017327 NM_019128 NM_019204 NM_019275 NM_019351 NM_019375 NM_020075 NM_020088 NM_021597 NM_021678 NM_021767 NM_021835 NM_021847 NM_022254 NM_022380 NM_022690 NM_022703 NM_022850 NM_022946 NM_023020 NM_023983 NM_024366 NM_024397 NM_030871 NM_031028 NM_031036 NM_031081 NM_031515 NM_031535 NM_031608 NM_031665 NM_031743 NM_032613 NM_053311 NM_053369 NM_053424 NM_053457 NM_053475 NM_053508 NM_053589 NM_053859 NM_053878 NM_053891 NM_053910 NM_057116 NM_080482 NM_080583 NM_080904 NM_131907 NM_133395 NM_133579 NM_134413 NM_138502 NM_138509 NM_138896 NM_139060 NM_139189 NM_139217 NM_144756 NM_148891 NM_153309 NM_153317 NM_173152 NM_181550 XM_213626 XM_213746 XM_213969 XM_214253 XM_215403 XM_215467 XM_215578 XM_215919 XM_215990 XM_217021 XM_218828 XM_220232 XM_221426 XM_223205 XM_223837 XM_224474 XM_227623 XM_228644 XM_233798 XM_234901 XM_235179 XM_236268 XM_236362 XM_237241 XM_238072 XM_238336 XM_241981 XM_340747 XM_341081 XM_341104 XM_341201 XM_341341 XM_341857 XM_341961 XM_342521 XM_342535 XM_342682 XM_342684 XM_342808 XM_343059 XM_343109 XM_343157 XM_343427 XM_343483 XM_343513 XM_343582 XM_343630 XM_343736 XM_343764 XM_573205 XM_573259 XM_573634 XM_576311 XM_579869 UniGene ID Rn.122667 Rn.78244

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 14

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 14 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 14 CA3 - AU ANOVA NEGATIVE CORRELATION GENBANK ® ID NM_001003978 NM_001004075 NM_001006991 NM_001011905 NM_001011992 NM_001012160 NM_001013206 NM_001013224 NM_001013234 NM_001013873 NM_012645 NM_013154 NM_019364 NM_020308 NM_022210 NM_022394 NM_022541 NM_024374 NM_024385 NM_031062 NM_031345 NM_031596 NM_031978 NM_032079 NM_053295 NM_053442 NM_053539 NM_053642 NM_053713 NM_053714 NM_053787 NM_130413 NM_134326 NM_134456 NM_145778 NM_145785 NM_171995 NM_173117 NM_175579 NM_182816 XM_213658 XM_213993 XM_214730 XM_214890 XM_215637 XM_215908 XM_216380 XM_216661 XM_217050 XM_219297 XM_221050 XM_224588 XM_231052 XM_232168 XM_232860 XM_233767 XM_235051 XM_236210 XM_237828 XM_243652 XM_340911 XM_341750 XM_342032 XM_342044 XM_342396 XM_342578 XM_345160 XM_578548

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 15

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 15 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 15 CA3 - AU ANOVA INCREASE GENBANK ® ID BF287008 AF442812 AY597251 NM_001002854 NM_001004199 NM_001004443 NM_001005557 NM_001006602 NM_001006976 NM_001007686 NM_001007734 NM_001008309 NM_001008515 NM_001008521 NM_001009349 NM_001009369 NM_001009632 NM_001009641 NM_001009645 NM_001009973 NM_001011896 NM_001011948 NM_001012021 NM_001012133 NM_001013033 NM_001013082 NM_001013213 NM_001013223 NM_001013233 NM_012512 NM_012550 NM_012562 NM_012656 NM_012731 NM_012857 NM_012870 NM_012887 NM_012895 NM_012904 NM_012935 NM_012939 NM_012940 NM_012988 NM_013001 NM_013022 NM_013055 NM_017116 NM_017264 NM_019238 NM_021763 NM_021846 NM_021863 NM_021997 NM_022197 NM_022219 NM_022282 NM_022515 NM_022599 NM_022626 NM_022941 NM_022949 NM_024144 NM_024150 NM_024377 NM_024388 NM_031078 NM_031083 NM_031094 NM_031122 NM_031622 NM_031640 NM_031721 NM_031728 NM_031751 NM_032612 NM_033096 NM_052809 NM_053455 NM_053541 NM_053580 NM_053584 NM_053698 NM_053774 NM_053826 NM_053832 NM_053884 NM_053946 NM_053998 NM_130409 NM_133314 NM_133387 NM_133548 NM_133552 NM_134389 NM_138508 NM_138846 NM_138847 NM_138907 NM_139083 NM_139094 NM_145783 NM_148890 NM_172324 NM_173323 NM_175756 NM_175762 NM_177933 NM_181432 NM_181628 NM_182844 NM_183331 NM_183402 NM_199111 NM_201988 U31866 XM_213324 XM_213346 XM_213418 XM_213823 XM_214958 XM_215037 XM_215469 XM_215528 XM_215812 XM_215858 XM_216316 XM_216757 XM_218041 XM_218759 XM_220606 XM_220736 XM_221077 XM_222152 XM_223508 XM_223684 XM_224971 XM_225039 XM_225644 XM_226769 XM_228197 XM_228305 XM_232202 XM_232466 XM_232608 XM_233138 XM_233341 XM_233611 XM_233820 XM_233944 XM_234328 XM_234441 XM_238163 XM_242005 XM_242556 XM_340943 XM_341066 XM_341251 XM_341346 XM_341444 XM_341644 XM_341688 XM_342002 XM_342154 XM_342470 XM_343126 XM_343318 XM_345114 XM_574371 XM_579460 XM_579522 UniGene ID Rn.14733

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 16

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 16 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 16 CA3 - AU ANOVA DECREASE GENBANK ® ID AI171809 BI395698 NM_001004083 NM_001006971 NM_001007616 NM_001008519 NM_001008694 NM_001009681 NM_001011930 NM_001011938 NM_001011939 NM_001012004 NM_001012175 NM_001012189 NM_001012345 NM_001013045 NM_001013094 NM_001013096 NM_001013138 NM_001013186 NM_012506 NM_012508 NM_012545 NM_012569 NM_012581 NM_012673 NM_012686 NM_012756 NM_012798 NM_012820 NM_012830 NM_012841 NM_012918 NM_013116 NM_013181 NM_013189 NM_016990 NM_017093 NM_017094 NM_017131 NM_017204 NM_017253 NM_017254 NM_017259 NM_017298 NM_017312 NM_019159 NM_019208 NM_019295 NM_019306 NM_019343 NM_020094 NM_021748 NM_021775 NM_021859 NM_022193 NM_022206 NM_022217 NM_022252 NM_022267 NM_022382 NM_022384 NM_022589 NM_022606 NM_022666 NM_022668 NM_022675 NM_022855 NM_022864 NM_022945 NM_023988 NM_024000 NM_024146 NM_024394 NM_030858 NM_030862 NM_031008 NM_031315 NM_031353 NM_031568 NM_031657 NM_031667 NM_031821 NM_031831 NM_053335 NM_053440 NM_053464 NM_053503 NM_053553 NM_053675 NM_053721 NM_053724 NM_053777 NM_053788 NM_053811 NM_053864 NM_053894 NM_053895 NM_053903 NM_053924 NM_053931 NM_053997 NM_057118 NM_057125 NM_057140 NM_057152 NM_057201 NM_080885 NM_133406 NM_133419 NM_133535 NM_133567 NM_133582 NM_134366 NM_134376 NM_134398 NM_134455 NM_134458 NM_134461 NM_139329 NM_139330 NM_139333 NM_145089 NM_145090 NM_145680 NM_147209 NM_148889 NM_173105 NM_175708 NM_175754 NM_175760 NM_175761 NM_175869 NM_177481 NM_178106 NM_181478 NM_181822 NM_182842 NM_199372 NM_199397 NM_212458 XM_213574 XM_213777 XM_213842 XM_213925 XM_213954 XM_213963 XM_214751 XM_214780 XM_214888 XM_215182 XM_215371 XM_215655 XM_215963 XM_215984 XM_216152 XM_216228 XM_216349 XM_216398 XM_216725 XM_216965 XM_217078 XM_217283 XM_217381 XM_217388 XM_218615 XM_220055 XM_220062 XM_220224 XM_220315 XM_222103 XM_222177 XM_222245 XM_222773 XM_224713 XM_225468 XM_227282 XM_227409 XM_227428 XM_228753 XM_230814 XM_230899 XM_232351 XM_233737 XM_233839 XM_235064 XM_235156 XM_235496 XM_235662 XM_236009 XM_236735 XM_238398 XM_340886 XM_341091 XM_341248 XM_341500 XM_341807 XM_343114 XM_343175 XM_343339 XM_343839 XM_345861 XM_573915 XM_575018 XM_575080 XM_579523 XM_579696 UniGene ID Rn.129749 Rn.116507

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 17

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 17 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 17 DG - AI ANOVA POSITIVE CORRELATION GENBANK ® ID NM_001001516 NM_001004080 NM_001004081 NM_001004199 NM_001004209 NM_001004225 NM_001004247 NM_001004273 NM_001004275 NM_001005539 NM_001006987 NM_001006998 NM_001007684 NM_001007691 NM_001008312 NM_001008324 NM_001008374 NM_001009618 NM_001009677 NM_001009708 NM_001011890 NM_001011910 NM_001011946 NM_001011999 NM_001012137 NM_001012149 NM_001012235 NM_001013105 NM_001013167 NM_001013175 NM_001013206 NM_001013213 NM_001013874 NM_001017385 NM_012543 NM_012577 NM_012628 NM_012686 NM_012701 NM_012749 NM_012777 NM_012781 NM_012788 NM_012820 NM_012893 NM_013000 NM_013015 NM_013107 NM_013135 NM_017051 NM_017052 NM_017068 NM_017075 NM_017109 NM_017142 NM_017181 NM_017232 NM_017288 NM_019124 NM_019131 NM_019159 NM_019204 NM_019257 NM_019359 NM_020308 NM_021766 NM_021869 NM_022400 NM_022499 NM_022500 NM_022502 NM_022523 NM_022539 NM_022592 NM_022595 NM_022596 NM_022617 NM_022637 NM_022853 NM_024359 NM_024400 NM_030859 NM_031035 NM_031049 NM_031057 NM_031101 NM_031105 NM_031120 NM_031357 NM_031514 NM_031576 NM_031587 NM_031599 NM_031632 NM_031654 NM_031725 NM_031798 NM_032612 NM_053295 NM_053418 NM_053588 NM_053598 NM_053612 NM_053670 NM_053698 NM_053777 NM_053870 NM_053945 NM_057114 NM_080888 NM_130416 NM_130420 NM_130894 NM_133551 NM_133557 NM_134367 NM_134370 NM_138508 NM_138900 NM_138917 NM_139107 NM_139186 NM_147210 NM_153469 NM_172063 NM_172068 NM_173111 NM_175578 NM_175582 NM_199119 NM_207591 NM_207602 XM_214172 XM_214383 XM_214518 XM_214588 XM_214968 XM_215069 XM_215371 XM_215754 XM_215939 XM_216641 XM_216740 XM_216872 XM_218425 XM_219374 XM_220264 XM_220699 XM_221387 XM_223190 XM_224944 XM_225726 XM_227066 XM_228114 XM_230637 XM_232323 XM_240330 XM_341249 XM_341785 XM_341957 XM_342092 XM_342318 XM_342757 XM_342887 XM_343119 XM_343318 XM_343773 XM_345674 XM_346244 XM_346854 XM_573772 XM_574670 XM_579675

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 18

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 18 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 18 DG - AI ANOVA NEGATIVE CORRELATION GENBANK ® ID AI043800 NM_001001512 NM_001004208 NM_001004446 NM_001008353 NM_001008520 NM_001011923 NM_001012025 NM_001012072 NM_001013873 NM_001015021 NM_012590 NM_012609 NM_012727 NM_012769 NM_012874 NM_012959 NM_012994 NM_013083 NM_013131 NM_017290 NM_019128 NM_019347 NM_020089 NM_021758 NM_021842 NM_022281 NM_022289 NM_022297 NM_022387 NM_022506 NM_022541 NM_022546 NM_022599 NM_022934 NM_022938 NM_023977 NM_024373 NM_024375 NM_031016 NM_031123 NM_031510 NM_031613 NM_031685 NM_031694 NM_031730 NM_053321 NM_053328 NM_053349 NM_053358 NM_053360 NM_053625 NM_053669 NM_053787 NM_053883 NM_080899 NM_080902 NM_131907 NM_138506 NM_138850 NM_138911 NM_138914 NM_139192 NM_139259 NM_144758 NM_145184 NM_153317 NM_172034 NM_172062 NM_173117 NM_173119 NM_173137 NM_176857 NM_181626 NM_199106 NM_201560 XM_213762 XM_213963 XM_213969 XM_215883 XM_215890 XM_218226 XM_218515 XM_219879 XM_220708 XM_220992 XM_222103 XM_222717 XM_222773 XM_224733 XM_225895 XM_231148 XM_232413 XM_234011 XM_234470 XM_236210 XM_236614 XM_241375 XM_341089 XM_341091 XM_341106 XM_341310 XM_342044 XM_342325 XM_342612 XM_342643 XM_343263 XM_343442 XM_344785 XM_345981 XM_574916 XM_576437 UniGene ID Rn.18726

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 19

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 19 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 19 DG - AI ANOVA INCREASE GENBANK ® ID BI303253 BF567886 BE112341 AW142720 AI231999 BF398752 AF030087 AY190520 NM_001002016 NM_001004076 NM_001004099 NM_001004218 NM_001005907 NM_001006989 NM_001007557 NM_001007625 NM_001007654 NM_001007712 NM_001007729 NM_001007749 NM_001008287 NM_001008725 NM_001008767 NM_001008768 NM_001009474 NM_001009502 NM_001009662 NM_001009669 NM_001009719 NM_001011985 NM_001012004 NM_001012088 NM_001012147 NM_001012162 NM_001013044 NM_001013112 NM_001013121 NM_001013179 NM_001013194 NM_001013210 NM_001013233 NM_001013249 NM_012512 NM_012546 NM_012562 NM_012581 NM_012637 NM_012663 NM_012762 NM_012844 NM_012862 NM_012913 NM_012925 NM_012939 NM_012971 NM_012974 NM_012985 NM_012992 NM_012993 NM_013044 NM_013070 NM_013122 NM_013137 NM_013146 NM_013156 NM_013194 NM_017060 NM_017116 NM_017125 NM_017132 NM_017175 NM_017192 NM_017200 NM_017280 NM_017307 NM_017320 NM_017351 NM_019156 NM_019232 NM_019249 NM_019253 NM_019289 NM_019312 NM_019363 NM_019904 NM_019906 NM_020073 NM_020074 NM_020075 NM_020088 NM_020099 NM_021690 NM_021769 NM_021909 NM_022210 NM_022226 NM_022270 NM_022382 NM_022390 NM_022526 NM_022530 NM_022531 NM_022601 NM_022638 NM_022692 NM_023967 NM_024155 NM_024353 NM_024358 NM_024369 NM_030826 NM_030831 NM_030863 NM_031013 NM_031099 NM_031114 NM_031140 NM_031328 NM_031509 NM_031511 NM_031525 NM_031544 NM_031593 NM_031677 NM_031683 NM_031778 NM_031789 NM_031797 NM_031818 NM_032067 NM_032416 NM_052983 NM_053314 NM_053356 NM_053404 NM_053411 NM_053455 NM_053485 NM_053516 NM_053560 NM_053583 NM_053584 NM_053592 NM_053618 NM_053714 NM_053783 NM_053886 NM_053896 NM_053927 NM_053936 NM_053999 NM_05710 NM_057197 NM_080480 NM_080584 NM_080691 NM_080698 NM_130409 NM_133296 NM_133298 NM_133305 NM_133605 NM_134449 NM_138542 NM_138855 NM_139110 NM_139216 NM_139327 NM_153297 NM_153628 NM_172029 NM_172033 NM_172325 NM_173118 NM_173123 NM_175756 NM_177426 NM_181365 NM_183328 NM_198134 NM_198786 NM_199093 NM_199115 NM_199118 NM_199378 NM_199388 NM_207598 NM_212463 NM_212501 XM_213972 XM_213995 XM_214441 XM_214656 XM_214927 XM_215095 XM_215222 XM_215285 XM_215576 XM_215733 XM_215840 XM_215935 XM_215942 XM_215994 XM_216410 XM_217061 XM_217152 XM_217154 XM_217271 XM_217283 XM_217297 XM_217367 XM_217690 XM_218292 XM_218816 XM_220567 XM_220736 XM_220810 XM_220982 XM_222476 XM_223524 XM_223583 XM_223690 XM_223781 XM_224969 XM_225014 XM_225259 XM_226016 XM_226211 XM_228073 XM_231620 XM_233138 XM_233345 XM_235518 XM_236380 XM_236675 XM_237371 XM_237825 XM_242644 XM_243637 XM_341107 XM_341227 XM_341352 XM_341574 XM_341578 XM_341653 XM_341657 XM_341664 XM_341790 XM_341948 XM_342007 XM_342048 XM_342409 XM_342542 XM_342591 XM_342759 XM_343006 XM_343065 XM_343126 XM_343166 XM_343174 XM_343198 XM_343332 XM_343564 XM_343570 XM_343845 XM_346594 XM_574170 XM_574618 XM_575585 UniGene ID Rn.105382 Rn.108166 Rn.114169 Rn.128732 Rn.24825 Rn.48866

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 20

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 20 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 20 DG - AI ANOVA DECREASE GENBANK ® ID BG381750 BM391206 BG374818 AI406842 BM388719 BE103926 NM_001001508 NM_001002819 NM_001003978 NM_001004082 NM_001004133 NM_001005765 NM_001006970 NM_001007680 NM_001007742 NM_001008299 NM_001008317 NM_001009679 NM_001009704 NM_001012017 NM_001012131 NM_001012150 NM_001012197 NM_001012214 NM_001013035 NM_001013092 NM_001013128 NM_001014187 NM_012585 NM_012916 NM_012934 NM_013002 NM_013060 NM_013066 NM_013111 NM_013192 NM_017011 NM_017093 NM_017105 NM_017155 NM_017171 NM_017215 NM_017303 NM_017311 NM_017318 NM_017328 NM_017357 NM_017359 NM_019356 NM_021597 NM_021849 NM_022188 NM_022254 NM_022262 NM_022264 NM_022532 NM_022548 NM_022615 NM_022668 NM_022678 NM_022688 NM_022962 NM_024484 NM_030842 NM_030846 NM_030871 NM_031005 NM_031054 NM_031325 NM_031563 NM_031573 NM_031596 NM_031727 NM_031777 NM_031977 NM_052801 NM_053492 NM_053589 NM_053642 NM_053729 NM_053779 NM_053801 NM_053834 NM_053851 NM_053891 NM_053931 NM_057208 NM_080482 NM_080776 NM_080781 NM_130749 NM_133425 NM_133562 NM_133568 NM_133596 NM_134376 NM_134395 NM_134398 NM_138849 NM_138922 NM_139091 NM_145676 NM_145783 NM_153318 NM_172008 NM_173133 NM_173337 NM_183331 NM_198787 NM_207590 XM_213610 XM_213765 XM_214155 XM_214690 XM_214856 XM_215134 XM_215573 XM_215896 XM_216047 XM_216227 XM_217063 XM_217115 XM_217147 XM_217464 XM_218660 XM_219576 XM_220992 XM_221888 XM_221910 XM_221962 XM_222946 XM_223729 XM_224335 XM_224588 XM_224707 XM_224713 XM_225138 XM_225468 XM_226888 XM_232197 XM_232760 XM_235705 XM_237288 XM_239171 XM_340739 XM_340856 XM_340999 XM_341112 XM_341337 XM_341683 XM_341688 XM_341803 XM_342134 XM_342763 XM_342854 XM_342920 XM_343358 XM_343395 XM_343469 XM_343910 XM_344063 XM_344594 XM_344744 NM_134383 NM_053410 XM_579362 UniGene ID Rn.101929 Rn.11688 Rn.39092 Rn.6994 Rn.8562 Rn.98343

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 21

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 21 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 21 DG - AU ANOVA POSITIVE CORRELATION GENBANK ® ID AF022087 NM_001001514 NM_001005534 NM_001005547 NM_001008301 NM_001009825 NM_001010953 NM_001011895 NM_001011920 NM_001011941 NM_001011990 NM_012634 NM_017346 NM_019379 NM_022675 NM_022936 NM_031034 NM_031575 NM_031631 NM_031735 NM_052981 NM_053440 NM_053639 NM_053804 NM_053842 NM_053871 NM_053965 NM_057141 NM_080478 NM_130406 NM_133313 NM_152935 NM_183402 NM_184049 NM_198785 NM_199380 X76489 XM_213421 XM_213484 XM_213782 XM_213824 XM_214035 XM_214420 XM_216349 XM_216661 XM_220574 XM_220754 XM_227749 XM_232531 XM_232809 XM_233341 XM_236181 XM_236992 XM_340970 XM_341550 XM_341666 XM_341796 XM_342300 XM_342592 XM_342686 XM_343513

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 22

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 22 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 22 DG - AU ANOVA NEGATIVE CORRELATION GENBANK ® ID NM_001004075 NM_001004200 NM_001005529 NM_001007146 NM_001008511 NM_001008885 NM_001011959 NM_001012034 NM_001012140 NM_001013065 NM_001013165 NM_001013198 NM_001017382 NM_012630 NM_012775 NM_012806 NM_012953 NM_012955 NM_012991 NM_013031 NM_013094 NM_013159 NM_013189 NM_017158 NM_017319 NM_019123 NM_019149 NM_019168 NM_019349 NM_021688 NM_021774 NM_022946 NM_024394 NM_030872 NM_031036 NM_031131 NM_031354 NM_031569 NM_053499 NM_053733 NM_053961 NM_054006 NM_133411 NM_134326 NM_134373 NM_172039 NM_172317 NM_175604 NM_175764 NM_182737 NM_198750 NM_199111 NM_199400 NM_199463 NM_212496 XM_213749 XM_214344 XM_215286 XM_215813 XM_216025 XM_216548 XM_216784 XM_217359 XM_218459 XM_218523 XM_219349 XM_222242 XM_223938 XM_224256 XM_224947 XM_225168 XM_225717 XM_227090 XM_230303 XM_230616 XM_232735 XM_233141 XM_235185 XM_235662 XM_239329 XM_242005 XM_340742 XM_341312 XM_341842 XM_342392 XM_342828 XM_343175 XM_343278 XM_343535 XM_343559 XM_347168 XM_573428 XM_576252 XM_579545

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 23

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 23 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 23 DG - AU ANOVA INCREASE GENBANK ® ID AF452647 NM_001004230 NM_001004279 NM_001004449 NM_001005565 NM_001007011 NM_001007613 NM_001007637 NM_001007739 NM_001008309 NM_001008316 NM_001008339 NM_001008515 NM_001008521 NM_001009619 NM_001009653 NM_001010965 NM_001011942 NM_001011979 NM_001012159 NM_001012174 NM_001013036 NM_001013163 NM_012576 NM_012583 NM_012774 NM_012858 NM_012935 NM_013220 NM_016994 NM_017138 NM_017263 NM_017294 NM_019170 NM_019251 NM_019302 NM_019374 NM_019623 NM_021262 NM_021264 NM_022236 NM_022269 NM_022398 NM_022515 NM_022694 NM_022709 NM_022961 NM_024125 NM_024139 NM_030844 NM_030858 NM_031028 NM_031138 NM_031518 NM_031597 NM_031822 NM_053402 NM_053421 NM_053502 NM_053613 NM_053621 NM_053826 NM_053876 NM_053901 NM_057152 NM_057196 NM_057204 NM_130740 NM_133405 NM_134356 NM_134411 NM_134432 NM_134457 NM_138889 NM_139253 NM_153316 NM_173837 NM_175598 NM_178101 NM_198751 NM_212525 NM_213567 XM_213240 XM_213336 XM_213992 XM_214720 XM_214895 XM_215184 XM_215372 XM_215424 XM_215566 XM_215602 XM_215949 XM_216112 XM_216191 XM_216515 XM_217326 XM_217825 XM_217837 XM_219045 XM_220506 XM_220606 XM_221030 XM_221635 XM_222251 XM_222832 XM_225866 XM_226237 XM_226722 XM_230846 XM_230856 XM_231552 XM_232855 XM_233377 XM_233535 XM_233679 XM_234017 XM_234441 XM_237291 XM_238063 XM_240417 XM_340918 XM_341239 XM_341857 XM_341950 XM_342141 XM_342312 XM_342398 XM_342579 XM_342662 XM_343446 XM_574233 XM_577170

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 24

An ANOVA was conducted on the probe set signal values for all present probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 24 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 24 DG - AU ANOVA DECREASE GENBANK ® ID BF564995 BM389079 AI171599 NM_001000510 NM_001001515 NM_001001799 NM_001004132 NM_001005381 NM_001005876 NM_001005879 NM_001006968 NM_001006994 NM_001007667 NM_001008331 NM_001009652 NM_001011891 NM_001012053 NM_001012083 NM_001012175 NM_001013090 NM_001013153 NM_012568 NM_012740 NM_012798 NM_012809 NM_012829 NM_017063 NM_017066 NM_017197 NM_017201 NM_017305 NM_017321 NM_019185 NM_021671 NM_021751 NM_021770 NM_022217 NM_022282 NM_022589 NM_022690 NM_022863 NM_022928 NM_023991 NM_024000 NM_024146 NM_024159 NM_030861 NM_030994 NM_031022 NM_031043 NM_031235 NM_031351 NM_031356 NM_031520 NM_031594 NM_031646 NM_032062 NM_032072 NM_032616 NM_053448 NM_053542 NM_053868 NM_057201 NM_080886 NM_080887 NM_080895 NM_131906 NM_131914 NM_134468 NM_138840 NM_138858 NM_138891 NM_139254 NM_145089 NM_145785 NM_152790 NM_171994 NM_172157 NM_173120 NM_177481 NM_177927 NM_178095 NM_178847 NM_181388 NM_182674 NM_198764 NM_199097 XM_213270 XM_213591 XM_213779 XM_213954 XM_214238 XM_214709 XM_214751 XM_215286 XM_215403 XM_215574 XM_216102 XM_216400 XM_217078 XM_217732 XM_218502 XM_220805 XM_222111 XM_222152 XM_225983 XM_226789 XM_227025 XM_230967 XM_232640 XM_234483 XM_235156 XM_235179 XM_235940 XM_238151 XM_238213 XM_340775 XM_340802 XM_341058 XM_341104 XM_341497 XM_341558 XM_341584 XM_342477 XM_342588 XM_342682 XM_342863 XM_343273 XM_343415 XM_347236 XM_573983 XM_579546 NM_022250 UniGene ID Rn.17829 Rn.21816 Rn.22355

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 25

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 25 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 25 CA1 - AI ANOVA POSITIVE CORRELATION GENBANK ® ID AA800031 AI101331 AI639001 BG377379 BG662522 NM_001004209 NM_001005762 NM_001005898 NM_001007651 NM_001008322 NM_001008324 NM_001009600 NM_001011946 NM_001012079 NM_001012111 NM_001012126 NM_001012177 NM_001012223 NM_001013082 NM_001017386 NM_001017450 NM_001024371 NM_001024925 NM_001025419 NM_001029901 NM_001033852 NM_001034933 NM_012543 NM_012562 NM_012577 NM_012671 NM_012686 NM_012777 NM_012884 NM_013015 NM_013060 NM_013091 NM_013107 NM_013173 NM_013191 NM_013198 NM_013219 NM_017068 NM_017223 NM_017267 NM_017356 NM_019318 NM_019362 NM_021775 NM_022198 NM_022226 NM_022502 NM_022617 NM_023978 NM_024163 NM_030863 NM_030992 NM_031014 NM_031034 NM_031147 NM_031521 NM_031552 NM_031812 NM_032066 NM_033443 NM_053021 NM_053407 NM_053445 NM_053467 NM_053485 NM_053538 NM_053777 NM_053783 NM_053910 NM_054001 NM_057204 NM_080907 NM_133534 NM_134390 NM_138502 NM_138914 NM_145674 NM_152790 NM_173101 NM_175578 NM_175582 NM_181639 NM_207602 NM_207617 NM_212528 XM_213329 XM_214968 XM_215037 XM_215095 XM_216837 XM_219262 XM_222242 XM_224337 XM_225631 XM_227870 XM_228072 XM_232608 XM_238362 XM_341081 XM_341851 XM_341936 XM_341940 XM_342291 XM_342297 XM_342317 XM_342521 XM_343274 XM_343468 XM_343773 XM_343776 XM_344421 XM_573100

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 26

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 26 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 26 CA1 - AI ANOVA NEGATIVE CORRELATION GENBANK ® ID AI227598 AW529408 BF397258 NM_001005381 NM_001008354 NM_001008557 NM_001010946 NM_001012012 NM_001012021 NM_001012187 NM_001012195 NM_001013198 NM_001017376 NM_001025271 NM_001025711 NM_001025738 NM_001033701 NM_012736 NM_013083 NM_013113 NM_017030 NM_017059 NM_019128 NM_019142 NM_019194 NM_021840 NM_022229 NM_022289 NM_022300 NM_022615 NM_031069 NM_031315 NM_031707 NM_031821 NM_053316 NM_053410 NM_053434 NM_053633 NM_053698 NM_053713 NM_053849 NM_053883 NM_080402 NM_133580 NM_138838 NM_138911 NM_139060 NM_139091 NM_172034 NM_199394 NM_199463 NM_213627 XM_213658 XM_214245 XM_214369 XM_214697 XM_215826 XM_216102 XM_216679 XM_216762 XM_216884 XM_217115 XM_217210 XM_218506 XM_219500 XM_219525 XM_221333 XM_221635 XM_223693 XM_224389 XM_224929 XM_225039 XM_232936 XM_234385 XM_235179 XM_235552 XM_235878 XM_236953 XM_242556 XM_243390 XM_340809 XM_341663 XM_342107 XM_342179 XM_342763 XM_342930 XM_343046 XM_343326 XM_343574 XM_343761 XM_344130 XM_345861 XM_345981 XM_573165 XM_575396 XM_577023

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 27

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 27 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 27 CA1 - AI ANOVA INCREASE GENBANK ® ID AI012566 AI170346 AI179982 AI410079 AI717047 BF396482 BF417285 BG672075 BG673602 BM392140 L26525 NM_001001511 NM_001001513 NM_001001800 NM_001004072 NM_001004081 NM_001004226 NM_001004250 NM_001004273 NM_001005534 NM_001005539 NM_001005565 NM_001006989 NM_001007000 NM_001007617 NM_001007624 NM_001007625 NM_001007629 NM_001007654 NM_001007665 NM_001007677 NM_001007682 NM_001008344 NM_001008365 NM_001008374 NM_001008829 NM_001008835 NM_001009474 NM_001009623 NM_001011893 NM_001011903 NM_001011917 NM_001011920 NM_001011925 NM_001011959 NM_001011981 NM_001011989 NM_001011991 NM_001011993 NM_001012051 NM_001012057 NM_001012065 NM_001012222 NM_001012744 NM_001013081 NM_001013086 NM_001013087 NM_001013121 NM_001013137 NM_001013174 NM_001013179 NM_001013190 NM_001013240 NM_001017383 NM_001024247 NM_001024261 NM_001025056 NM_001025282 NM_001025289 NM_001025423 NM_001025648 NM_001025721 NM_001025722 NM_001031641 NM_001031644 NM_001033968 NM_001034004 NM_001034090 NM_001034164 NM_012488 NM_012497 NM_012512 NM_012512 NM_012531 NM_012595 NM_012645 NM_012671 NM_012703 NM_012747 NM_012749 NM_012771 NM_012815 NM_012819 NM_012823 NM_012837 NM_012838 NM_012925 NM_012939 NM_013001 NM_013044 NM_013055 NM_013069 NM_013137 NM_013157 NM_016986 NM_017008 NM_017009 NM_017014 NM_017113 NM_017125 NM_017132 NM_017154 NM_017160 NM_017169 NM_017177 NM_017181 NM_017193 NM_017196 NM_017257 NM_017264 NM_017274 NM_017288 NM_017320 NM_017333 NM_017348 NM_017351 NM_017356 NM_017359 NM_019238 NM_019289 NM_019290 NM_019346 NM_019358 NM_019359 NM_020082 NM_021576 NM_021690 NM_021989 NM_022266 NM_022285 NM_022381 NM_022390 NM_022392 NM_022500 NM_022510 NM_022512 NM_022525 NM_022526 NM_022597 NM_022602 NM_022668 NM_022697 NM_022703 NM_022856 NM_024155 NM_024160 NM_024366 NM_024396 NM_030826 NM_030859 NM_030872 NM_030987 NM_031057 NM_031090 NM_031140 NM_031357 NM_031509 NM_031614 NM_031624 NM_031648 NM_031660 NM_031668 NM_031672 NM_031685 NM_031698 NM_031756 NM_031789 NM_031818 NM_031827 NM_031841 NM_031973 NM_040669 NM_053323 NM_053442 NM_053455 NM_053516 NM_053536 NM_053553 NM_053554 NM_053560 NM_053597 NM_053612 NM_053684 NM_053773 NM_053794 NM_053838 NM_053959 NM_053979 NM_053985 NM_054006 NM_057114 NM_057137 NM_057197 NM_080887 NM_080890 NM_130403 NM_130416 NM_130419 NM_130428 NM_130739 NM_133297 NM_133298 NM_133392 NM_133405 NM_133418 NM_133605 NM_133618 NM_133621 NM_134334 NM_134349 NM_134389 NM_134410 NM_134432 NM_138508 NM_138521 NM_138826 NM_138828 NM_138900 NM_138905 NM_138917 NM_139103 NM_139110 NM_139189 NM_139216 NM_139327 NM_145081 NM_145775 NM_147210 NM_153621 NM_153628 NM_172033 NM_172038 NM_172222 NM_172335 NM_173095 NM_173118 NM_173123 NM_173147 NM_175756 NM_175838 NM_176077 NM_178095 NM_181363 NM_181381 NM_181628 NM_183330 NM_184046 NM_198738 NM_199087 NM_199092 NM_199118 NM_199399 NM_199404 NM_207591 NM_207599 NM_207609 NM_212495 NM_212525 NM_212538 XM_213335 XM_213408 XM_213540 XM_213650 XM_213777 XM_213824 XM_213879 XM_214250 XM_214316 XM_214478 XM_214480 XM_214518 XM_214583 XM_214769 XM_214838 XM_215524 XM_215607 XM_215733 XM_215897 XM_216565 XM_216688 XM_216704 XM_216740 XM_216962 XM_217239 XM_217335 XM_217372 XM_218617 XM_218816 XM_218977 XM_219948 XM_220095 XM_220357 XM_220541 XM_221100 XM_223012 XM_223785 XM_224535 XM_224538 XM_225014 XM_225147 XM_225160 XM_225628 XM_225644 XM_225711 XM_226165 XM_228701 XM_230036 XM_230291 XM_231287 XM_231620 XM_231749 XM_235497 XM_235558 XM_235710 XM_237381 XM_237790 XM_238019 XM_238380 XM_238770 XM_243637 XM_341389 XM_341509 XM_341796 XM_341882 XM_341957 XM_342002 XM_342300 XM_342528 XM_342600 XM_342686 XM_343034 XM_343259 XM_343268 XM_343306 XM_343396 XM_343427 XM_344524 XM_345535 XM_345584 XM_345825 XM_345849 XM_345870 XM_347163 XM_575585 XM_576343 XM_576401 XM_576459

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 28

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged

Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 28 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 28 CA1 - AI ANOVA DECREASE GENBANK ® ID AF073379 AI029288 AI229643 AI599699 AW528891 BE118251 BF404393 BF410962 NM_001002289 NM_001002851 NM_001003957 NM_001004198 NM_001004210 NM_001004277 NM_001004279 NM_001004442 NM_001005536 NM_001005872 NM_001007728 NM_001008320 NM_001008353 NM_001009268 NM_001009605 NM_001011901 NM_001011966 NM_001012043 NM_001012143 NM_001012144 NM_001012211 NM_001012475 NM_001013066 NM_001013096 NM_001013099 NM_001013128 NM_001013133 NM_001013178 NM_001013244 NM_001014792 NM_001015011 NM_001024318 NM_001024766 NM_001024790 NM_001024794 NM_001025136 NM_001025402 NM_001025414 NM_001025650 NM_001025667 NM_001025705 NM_001033655 NM_001033699 NM_001033974 NM_001033984 NM_001034014 NM_001034068 NM_001034131 NM_012568 NM_012573 NM_012576 NM_012596 NM_012651 NM_012653 NM_012688 NM_012701 NM_012727 NM_012780 NM_012835 NM_012934 NM_012991 NM_013036 NM_013100 NM_013102 NM_013111 NM_013126 NM_013161 NM_013179 NM_013189 NM_013199 NM_017041 NM_017073 NM_017238 NM_017303 NM_017352 NM_019163 NM_019218 NM_019282 NM_019288 NM_019347 NM_019348 NM_020306 NM_021266 NM_021653 NM_021763 NM_021843 NM_022249 NM_022254 NM_022688 NM_022847 NM_022850 NM_022867 NM_022962 NM_023971 NM_023989 NM_024362 NM_024401 NM_031056 NM_031123 NM_031130 NM_031318 NM_031720 NM_031730 NM_031753 NM_031777 NM_031828 NM_033485 NM_053349 NM_053441 NM_053487 NM_053503 NM_053530 NM_053616 NM_053693 NM_053703 NM_053718 NM_053740 NM_053775 NM_053781 NM_053786 NM_053876 NM_053888 NM_053895 NM_054008 NM_057212 NM_130748 NM_133318 NM_133411 NM_133548 NM_133591 NM_133596 NM_134383 NM_134388 NM_138837 NM_138907 NM_138922 NM_144758 NM_147135 NM_147142 NM_153317 NM_173145 NM_177419 NM_181370 NM_181380 NM_182668 NM_182844 NM_198749 NM_198760 NM_198761 NM_198770 NM_199373 U48828 XM_213440 XM_213842 XM_213954 XM_214093 XM_214312 XM_214621 XM_214673 XM_214696 XM_214823 XM_214883 XM_215376 XM_215451 XM_215883 XM_215892 XM_215984 XM_216047 XM_216161 XM_216225 XM_216318 XM_217560 XM_217570 XM_217601 XM_218138 XM_218187 XM_218200 XM_218347 XM_218845 XM_219372 XM_219905 XM_221050 XM_221212 XM_221231 XM_221380 XM_221426 XM_221641 XM_221724 XM_221888 XM_221962 XM_222103 XM_222184 XM_222476 XM_222770 XM_223643 XM_223729 XM_225138 XM_225138 XM_225168 XM_225169 XM_225220 XM_226349 XM_226436 XM_226843 XM_226874 XM_227104 XM_227444 XM_227811 XM_230449 XM_230877 XM_231798 XM_231803 XM_232197 XM_232220 XM_232599 XM_233141 XM_233499 XM_233792 XM_234219 XM_234263 XM_234299 XM_234345 XM_234345 XM_234470 XM_234481 XM_234514 XM_234540 XM_234546 XM_235768 XM_239074 XM_239260 XM_341111 XM_341391 XM_341590 XM_341642 XM_341653 XM_341709 XM_342151 XM_342217 XM_342481 XM_342552 XM_342692 XM_342734 XM_342775 XM_342804 XM_342808 XM_343045 XM_343148 XM_343548 XM_344594 XM_345418 XM_345789 XM_574979 XM_575397

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 29

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 29 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 29 AU ANOVA POSITIVE CORRELATION GENBANK ® ID AA955871 BF288303 BF410275 NM_001002016 NM_001025403 NM_001025744 NM_001035233 NM_012623 NM_012660 NM_012869 NM_013159 NM_013176 NM_013197 NM_017007 NM_017103 NM_017294 NM_017306 NM_017347 NM_017354 NM_019183 NM_019239 NM_019309 NM_019351 NM_019354 NM_031097 NM_033359 NM_053383 NM_053644 NM_053669 NM_053721 NM_053811 NM_053824 NM_053930 NM_053972 NM_057208 NM_080577 NM_080786 NM_130406 NM_131906 NM_138848 NM_153469 NM_172041 NM_172224 NM_173325 XM_213564 XM_214400 XM_216018 XM_216784 XM_218336 XM_220775 XM_223057 XM_223227 XM_224618 XM_230288 XM_230616 XM_230765 XM_234508 XM_239329 XM_341972 XM_342003 XM_342723 XM_343303 XM_343764 XM_573915 XM_575671

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 30

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 30 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 30 CA1 - AU ANOVA NEGATIVE CORRELATION GENBANK ® ID BG378690 NM_001002830 NM_001004075 NM_001008382 NM_001008524 NM_001011936 NM_001013204 NM_001013212 NM_001033674 NM_001034129 NM_017089 NM_017271 NM_019161 NM_019364 NM_021262 NM_022921 NM_024002 NM_024131 NM_031041 NM_031082 NM_031122 NM_031133 NM_031139 NM_031642 NM_031645 NM_032058 NM_053389 NM_053499 NM_053500 NM_053578 NM_057207 NM_134395 NM_134408 NM_134417 NM_138536 NM_138856 NM_145677 NM_152861 NM_172243 XM_213725 XM_215082 XM_215616 XM_216295 XM_216400 XM_216712 XM_216841 XM_223674 XM_225726 XM_228197 XM_233467 XM_236745 XM_237179 XM_239510 XM_340856 XM_342131 XM_342268 XM_343318 XM_343413 XM_343513

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 31

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 31 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 31 CA1 - AU ANOVA INCREASE GENBANK ® ID AA859127 AA998007 AI137495 BF287008 BI294974 BM384139 BM388245 BM390128 NM_001004090 NM_001004238 NM_001004255 NM_001004443 NM_001005528 NM_001006969 NM_001007557 NM_001007609 NM_001007654 NM_001008339 NM_001008364 NM_001008515 NM_001009604 NM_001009973 NM_001009974 NM_001010961 NM_001011922 NM_001011950 NM_001011953 NM_001012003 NM_001012030 NM_001012039 NM_001012096 NM_001012105 NM_001012131 NM_001012181 NM_001012459 NM_001013151 NM_001013152 NM_001013154 NM_001013165 NM_001013165 NM_001013184 NM_001024964 NM_001025035 NM_001025137 NM_001025709 NM_001025725 NM_001030024 NM_001033866 NM_001034110 NM_012592 NM_012720 NM_012805 NM_012806 NM_012848 NM_012895 NM_012913 NM_012924 NM_012935 NM_012992 NM_013057 NM_013088 NM_013150 NM_013151 NM_016994 NM_017212 NM_017290 NM_017318 NM_019251 NM_019361 NM_021584 NM_021846 NM_022205 NM_022252 NM_022499 NM_022529 NM_022545 NM_024125 NM_024153 NM_031058 NM_031112 NM_031148 NM_031517 NM_031623 NM_031740 NM_031763 NM_053482 NM_053662 NM_053707 NM_053926 NM_057107 NM_057108 NM_057143 NM_057196 NM_080906 NM_080910 NM_130740 NM_131911 NM_131914 NM_133303 NM_134326 NM_138530 NM_138835 NM_138873 NM_145084 NM_145670 NM_145673 NM_145788 NM_147205 NM_153475 NM_172325 NM_175764 NM_182821 NM_182955 NM_201415 NM_212496 NM_213628 XM_213370 XM_213560 XM_213898 XM_213906 XM_214153 XM_214163 XM_214927 XM_215423 XM_215564 XM_215947 XM_215949 XM_216202 XM_216403 XM_216407 XM_216643 XM_216757 XM_216893 XM_217086 XM_218162 XM_218502 XM_218648 XM_219879 XM_219925 XM_220398 XM_221120 XM_221307 XM_223327 XM_223580 XM_223597 XM_224863 XM_225439 XM_226076 XM_226329 XM_230845 XM_233535 XM_233883 XM_234238 XM_234377 XM_234394 XM_235296 XM_236948 XM_237093 XM_238731 XM_340798 XM_341508 XM_341578 XM_342154 XM_342580 XM_342662 XM_342810 XM_342819 XM_343050 XM_344976 XM_574504 XM_575968 XM_578542

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 32

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 32 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 32 CA1 - AU ANOVA DECREASE GENBANK ® ID AA945615 AI764408 BE103926 BF403383 BF567766 BI287800 NM_001002815 NM_001004132 NM_001007607 NM_001007616 NM_001007629 NM_001007725 NM_001007758 NM_001008369 NM_001008823 NM_001009258 NM_001009405 NM_001011894 NM_001011995 NM_001012101 NM_001012191 NM_001012737 NM_001013044 NM_001013108 NM_001013161 NM_001013224 NM_001013432 NM_001013910 NM_001015004 NM_001017381 NM_001024756 NM_001024781 NM_001024795 NM_001024823 NM_001025032 NM_001025032 NM_001025416 NM_001025693 NM_001031656 NM_001031845 NM_001033757 NM_001033882 NM_001033951 NM_001034020 NM_001034133 NM_001034163 NM_001034849 NM_012504 NM_012555 NM_012572 NM_012598 NM_012654 NM_012774 NM_012853 NM_012863 NM_012877 NM_012950 NM_012983 NM_013002 NM_013127 NM_013160 NM_017049 NM_017134 NM_017139 NM_017239 NM_017256 NM_017316 NM_019140 NM_019156 NM_020074 NM_021659 NM_021859 NM_022202 NM_022382 NM_022396 NM_022600 NM_022609 NM_022676 NM_022690 NM_022853 NM_022946 NM_023972 NM_024147 NM_024355 NM_024356 NM_024383 NM_030862 NM_031008 NM_031037 NM_031046 NM_031073 NM_031132 NM_031332 NM_031353 NM_031356 NM_031511 NM_031528 NM_031569 NM_031571 NM_031575 NM_031617 NM_031738 NM_031771 NM_031967 NM_032062 NM_032613 NM_033097 NM_033376 NM_053306 NM_053310 NM_053360 NM_053428 NM_053559 NM_053594 NM_053599 NM_053601 NM_053643 NM_053655 NM_053686 NM_053764 NM_053788 NM_053801 NM_053842 NM_053846 NM_053859 NM_053870 NM_053960 NM_053994 NM_057213 NM_080394 NM_080580 NM_080885 NM_130829 NM_131913 NM_133397 NM_133410 NM_133511 NM_133566 NM_134331 NM_134377 NM_134461 NM_139104 NM_139263 NM_144740 NM_171992 NM_172039 NM_173115 NM_173146 NM_173312 NM_173837 NM_181092 NM_181638 NM_182673 NM_182824 NM_182842 NM_198758 NM_199111 NM_203338 NM_207592 X55812 XM_213318 XM_213993 XM_214630 XM_214669 XM_214720 XM_214775 XM_214916 XM_215469 XM_215742 XM_215887 XM_215939 XM_216189 XM_216745 XM_217021 XM_217124 XM_217188 XM_217279 XM_217388 XM_218412 XM_218851 XM_219529 XM_219801 XM_220224 XM_220602 XM_220884 XM_220982 XM_221672 XM_221977 XM_222223 XM_222896 XM_224261 XM_224952 XM_225259 XM_225625 XM_226213 XM_230296 XM_232488 XM_232640 XM_233231 XM_234205 XM_235426 XM_235500 XM_235640 XM_239504 XM_240330 XM_241981 XM_242982 XM_340775 XM_340911 XM_340967 XM_340999 XM_341790 XM_341998 XM_342032 XM_342134 XM_342389 XM_342409 XM_342632 XM_342905 XM_343058 XM_343247 XM_343394 XM_343459 XM_343483 XM_343582 XM_344434 XM_346464 XM_576183

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 33

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 33 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 33 CA3 - AI ANOVA POSITIVE CORRELATION GENBANK ® ID AA800192 AA892549 AA956317 AI103026 AI556426 BF398122 BI282114 BM391371 NM_001001511 NM_001002016 NM_001004080 NM_001004255 NM_001005765 NM_001007145 NM_001007677 NM_001007797 NM_001008316 NM_001008331 NM_001008374 NM_001008725 NM_001008767 NM_001008880 NM_001009474 NM_001010961 NM_001011893 NM_001011929 NM_001011946 NM_001011954 NM_001011991 NM_001012025 NM_001012040 NM_001012075 NM_001012097 NM_001012111 NM_001012137 NM_001012138 NM_001012150 NM_001012203 NM_001012215 NM_001012235 NM_001013110 NM_001013121 NM_001013130 NM_001013200 NM_001013246 NM_001015009 NM_001017386 NM_001017503 NM_001024238 NM_001024771 NM_001025125 NM_001025289 NM_001031647 NM_001033696 NM_001033701 NM_001033852 NM_001034090 NM_012507 NM_012514 NM_012543 NM_012569 NM_012577 NM_012618 NM_012655 NM_012671 NM_012720 NM_012720 NM_012747 NM_012749 NM_012777 NM_012778 NM_012804 NM_012816 NM_012825 NM_012894 NM_012920 NM_012925 NM_012963 NM_012983 NM_013005 NM_013044 NM_013045 NM_013058 NM_013060 NM_013065 NM_013096 NM_013137 NM_013176 NM_013198 NM_017006 NM_017031 NM_017037 NM_017041 NM_017068 NM_017073 NM_017092 NM_017148 NM_017166 NM_017197 NM_017206 NM_017223 NM_017251 NM_017261 NM_017307 NM_017333 NM_017354 NM_017357 NM_019161 NM_019168 NM_019175 NM_019204 NM_019257 NM_019321 NM_019359 NM_021595 NM_021682 NM_021762 NM_021868 NM_022207 NM_022238 NM_022276 NM_022285 NM_022390 NM_022799 NM_022861 NM_023978 NM_024398 NM_030832 NM_030868 NM_030872 NM_031031 NM_031033 NM_031034 NM_031035 NM_031049 NM_031087 NM_031091 NM_031092 NM_031093 NM_031140 NM_031144 NM_031521 NM_031552 NM_031665 NM_031841 NM_032990 NM_052807 NM_053021 NM_053323 NM_053328 NM_053369 NM_053424 NM_053467 NM_053475 NM_053502 NM_053576 NM_053598 NM_053612 NM_053681 NM_053735 NM_053757 NM_053766 NM_053799 NM_053824 NM_053926 NM_053936 NM_053985 NM_053994 NM_054001 NM_057114 NM_057148 NM_057197 NM_057200 NM_057208 NM_080691 NM_130403 NM_133317 NM_133398 NM_133548 NM_133560 NM_133602 NM_133605 NM_138905 NM_138914 NM_139038 NM_139103 NM_139330 NM_145092 NM_145670 NM_147210 NM_152790 NM_152847 NM_153308 NM_153311 NM_172033 NM_172068 NM_173152 NM_175578 NM_175582 NM_175838 NM_176857 NM_178095 NM_181388 NM_199119 XM_213329 XM_213408 XM_213421 XM_213746 XM_213779 XM_213849 XM_213920 XM_213966 XM_214029 XM_214371 XM_214518 XM_214583 XM_214968 XM_215080 XM_215095 XM_215184 XM_215367 XM_215469 XM_215733 XM_215872 XM_216386 XM_216688 XM_216704 XM_216759 XM_216965 XM_217192 XM_217367 XM_217372 XM_217409 XM_218162 XM_218816 XM_219998 XM_220207 XM_221100 XM_221497 XM_221562 XM_222024 XM_222617 XM_222661 XM_222745 XM_222780 XM_223227 XM_223583 XM_224256 XM_224337 XM_224732 XM_224852 XM_225008 XM_225014 XM_225160 XM_225404 XM_225512 XM_226165 XM_227203 XM_227409 XM_227581 XM_230036 XM_230592 XM_231287 XM_231620 XM_232354 XM_232671 XM_232732 XM_233761 XM_234328 XM_234345 XM_234377 XM_234468 XM_235064 XM_235657 XM_236362 XM_237042 XM_237241 XM_237381 XM_238019 XM_238057 XM_238103 XM_238213 XM_238362 XM_238649 XM_240978 XM_241375 XM_241671 XM_340810 XM_340879 XM_340997 XM_341052 XM_341172 XM_341215 XM_341288 XM_341538 XM_341605 XM_341633 XM_341882 XM_341911 XM_342100 XM_342102 XM_342291 XM_342297 XM_342317 XM_342521 XM_342535 XM_342626 XM_342662 XM_342928 XM_343055 XM_343092 XM_343157 XM_343268 XM_343274 XM_343281 XM_343427 XM_343570 XM_343630 XM_343764 XM_343773 XM_343856 XM_343971 XM_344046 XM_344785 XM_345446 XM_345584 XM_345825 XM_347166 XM_347223 XM_573100 XM_575396 XM_576311 XM_576343 XM_576401

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 34

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 34 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 34 CA3 - AI ANOVA NEGATIVE CORRELATION GENBANK ® ID BF282715 BM391206 NM_001001718 NM_001002818 NM_001003653 NM_001004075 NM_001004217 NM_001004222 NM_001005543 NM_001006602 NM_001006984 NM_001006994 NM_001007656 NM_001007707 NM_001008304 NM_001008511 NM_001008553 NM_001008557 NM_001009422 NM_001009666 NM_001009677 NM_001010946 NM_001011923 NM_001011934 NM_001011957 NM_001011996 NM_001012012 NM_001012098 NM_001012101 NM_001012125 NM_001012192 NM_001013133 NM_001013201 NM_001013906 NM_001014785 NM_001024250 NM_001024756 NM_001029898 NM_001031649 NM_001033069 NM_012500 NM_012600 NM_012739 NM_013083 NM_013090 NM_013111 NM_013113 NM_013130 NM_013174 NM_017126 NM_017135 NM_017352 NM_021688 NM_021699 NM_022186 NM_022188 NM_022264 NM_022272 NM_022511 NM_022599 NM_022688 NM_022860 NM_022938 NM_022941 NM_022948 NM_022961 NM_023104 NM_024366 NM_024381 NM_024390 NM_030830 NM_030841 NM_031006 NM_031030 NM_031062 NM_031070 NM_031344 NM_031520 NM_031569 NM_031583 NM_031742 NM_031749 NM_031851 NM_032079 NM_033349 NM_053334 NM_053388 NM_053528 NM_053575 NM_053613 NM_053621 NM_053622 NM_053792 NM_053810 NM_053849 NM_053883 NM_053950 NM_053990 NM_053997 NM_054008 NM_133394 NM_133425 NM_133562 NM_133596 NM_133596 NM_138833 NM_138866 NM_138893 NM_139254 NM_139337 NM_145098 NM_147141 NM_152861 NM_172062 NM_173094 NM_173115 NM_178091 NM_182844 NM_184051 NM_198726 NM_198756 NM_198783 NM_199098 NM_199500 NM_206881 NM_212496 NM_212544 XM_213426 XM_213626 XM_213672 XM_214331 XM_214400 XM_214475 XM_214485 XM_214491 XM_214550 XM_214895 XM_215069 XM_215082 XM_215134 XM_215826 XM_215883 XM_215931 XM_216112 XM_217385 XM_217908 XM_218851 XM_219796 XM_220219 XM_221270 XM_221304 XM_221627 XM_221833 XM_221910 XM_222717 XM_223327 XM_223693 XM_223921 XM_225039 XM_225072 XM_226843 XM_227414 XM_227428 XM_232735 XM_232745 XM_232901 XM_233544 XM_234219 XM_235295 XM_235878 XM_236614 XM_240178 XM_340884 XM_340889 XM_341015 XM_341249 XM_341314 XM_341326 XM_341520 XM_341663 XM_341955 XM_341969 XM_342107 XM_342295 XM_342692 XM_343140 XM_343413 XM_343429 XM_343614 XM_344009 XM_344168 XM_344426 XM_345668 XM_345848 XM_346887

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 35

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 35 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 35 CA3 - AI ANOVA INCREASE GENBANK ® ID AI029288 AI235284 AW535280 BE118404 BF288606 BI273920 BI274299 BM390128 NM_001001800 NM_001004068 NM_001004214 NM_001004239 NM_001005539 NM_001006963 NM_001007641 NM_001007712 NM_001007734 NM_001007739 NM_001007803 NM_001008312 NM_001008509 NM_001008861 NM_001008893 NM_001009239 NM_001009641 NM_001009660 NM_001009668 NM_001009683 NM_001011890 NM_001011910 NM_001011920 NM_001011970 NM_001011974 NM_001011989 NM_001012039 NM_001012057 NM_001012061 NM_001012067 NM_001012123 NM_001012162 NM_001012181 NM_001012201 NM_001012208 NM_001012217 NM_001012275 NM_001013087 NM_001013120 NM_001013179 NM_001013210 NM_001013213 NM_001013250 NM_001015026 NM_001024903 NM_001024925 NM_001025418 NM_001025423 NM_001025739 NM_001025744 NM_001031641 NM_001033683 NM_001033964 NM_001034004 NM_001034110 NM_001034157 NM_001034933 NM_001034999 NM_012519 NM_012532 NM_012555 NM_012573 NM_012703 NM_012713 NM_012717 NM_012722 NM_012775 NM_012788 NM_012806 NM_012842 NM_012884 NM_013015 NM_013016 NM_013029 NM_013047 NM_013070 NM_013086 NM_013088 NM_013091 NM_013107 NM_013132 NM_013164 NM_013191 NM_013194 NM_016989 NM_017009 NM_017013 NM_017015 NM_017024 NM_017052 NM_017060 NM_017062 NM_017109 NM_017125 NM_017137 NM_017181 NM_017193 NM_017196 NM_017200 NM_017212 NM_017234 NM_017259 NM_017274 NM_017289 NM_017320 NM_017347 NM_017351 NM_019160 NM_019242 NM_019249 NM_019269 NM_019358 NM_020082 NM_021264 NM_021695 NM_021989 NM_022178 NM_022281 NM_022401 NM_022500 NM_022502 NM_022516 NM_022592 NM_022617 NM_022677 NM_022699 NM_022800 NM_022853 NM_022856 NM_023025 NM_024001 NM_024155 NM_024372 NM_024396 NM_030871 NM_030989 NM_031005 NM_031018 NM_031027 NM_031099 NM_031107 NM_031132 NM_031321 NM_031357 NM_031509 NM_031576 NM_031620 NM_031648 NM_031672 NM_031677 NM_031694 NM_031797 NM_031806 NM_031818 NM_031827 NM_031970 NM_032067 NM_032462 NM_032619 NM_033097 NM_033230 NM_033443 NM_052981 NM_053434 NM_053442 NM_053493 NM_053506 NM_053516 NM_053550 NM_053553 NM_053560 NM_053599 NM_053633 NM_053639 NM_053796 NM_053840 NM_053893 NM_053895 NM_058211 NM_078622 NM_080584 NM_080688 NM_131911 NM_133298 NM_133303 NM_133307 NM_133511 NM_133534 NM_133545 NM_133598 NM_133611 NM_134334 NM_134349 NM_134390 NM_134408 NM_134453 NM_138520 NM_138828 NM_138832 NM_139043 NM_139105 NM_139110 NM_139216 NM_139255 NM_147136 NM_147206 NM_147207 NM_171992 NM_172030 NM_173116 NM_173118 NM_175595 NM_175843 NM_176075 NM_177419 NM_181475 NM_182821 NM_182843 NM_198743 NM_198787 NM_199093 NM_199118 NM_199388 NM_199499 NM_203366 NM_206950 NM_207609 NM_212523 NM_213563 NM_214457 XM_213688 XM_214035 XM_214480 XM_214958 XM_215076 XM_215177 XM_215466 XM_215576 XM_215607 XM_215757 XM_215935 XM_215949 XM_216004 XM_216407 XM_216565 XM_216717 XM_216872 XM_216910 XM_216968 XM_217062 XM_217188 XM_217254 XM_217263 XM_217441 XM_217570 XM_218293 XM_218336 XM_218382 XM_218617 XM_219296 XM_219539 XM_219785 XM_220175 XM_220333 XM_220805 XM_220918 XM_220986 XM_221307 XM_221387 XM_222911 XM_223781 XM_224474 XM_224535 XM_224561 XM_225020 XM_225147 XM_225628 XM_226510 XM_226874 XM_226987 XM_227066 XM_227870 XM_228044 XM_228073 XM_231566 XM_231620 XM_231650 XM_231763 XM_232809 XM_232865 XM_233603 XM_234281 XM_235480 XM_235552 XM_235558 XM_235609 XM_235710 XM_236009 XM_236020 XM_236196 XM_236560 XM_237371 XM_237415 XM_238205 XM_240311 XM_242032 XM_242644 XM_242982 XM_243637 XM_341111 XM_341133 XM_341877 XM_341940 XM_341957 XM_342002 XM_342052 XM_342218 XM_342286 XM_342397 XM_342800 XM_343259 XM_343303 XM_343396 XM_343412 XM_343479 XM_344524 XM_345535 XM_574504 XM_575585 XM_576238 XM_576459

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 36

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 36 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 36 CA3 - AI ANOVA DECREASE GENBANK ® ID AA943681 AI228348 AW524426 AW524733 BE103926 BF282660 BF407666 BG379941 BG380494 BI287800 NM_001002253 NM_001002828 NM_001003978 NM_001004078 NM_001004132 NM_001004133 NM_001004210 NM_001004227 NM_001004235 NM_001004250 NM_001004277 NM_001004279 NM_001004442 NM_001005884 NM_001005885 NM_001005905 NM_001005908 NM_001006970 NM_001006981 NM_001006997 NM_001007014 NM_001007149 NM_001007643 NM_001007720 NM_001007742 NM_001008299 NM_001008317 NM_001008382 NM_001008766 NM_001008888 NM_001009180 NM_001009258 NM_001009424 NM_001009536 NM_001009619 NM_001009640 NM_001009661 NM_001009719 NM_001009831 NM_001009967 NM_001010963 NM_001010965 NM_001011901 NM_001011906 NM_001011924 NM_001011932 NM_001011950 NM_001011951 NM_001011955 NM_001011966 NM_001011998 NM_001012017 NM_001012035 NM_001012038 NM_001012060 NM_001012068 NM_001012103 NM_001012119 NM_001012129 NM_001012144 NM_001012152 NM_001012187 NM_001012191 NM_001012195 NM_001012197 NM_001012473 NM_001012738 NM_001013058 NM_001013076 NM_001013170 NM_001013183 NM_001013189 NM_001013198 NM_001013218 NM_001013235 NM_001013426 NM_001013434 NM_001014793 NM_001017377 NM_001024261 NM_001024360 NM_001024754 NM_001025032 NM_001025114 NM_001025271 NM_001025411 NM_001025686 NM_001025696 NM_001025705 NM_001025738 NM_001029900 NM_001029910 NM_001030023 NM_001030029 NM_001030030 NM_001030037 NM_001031645 NM_001031659 NM_001033079 NM_001033674 NM_001033675 NM_001033679 NM_001033684 NM_001033702 NM_001033708 NM_001033715 NM_001033899 NM_001033974 NM_001034014 NM_001034083 NM_001034104 NM_001034112 NM_001034925 NM_001034937 NM_001034994 NM_001035001 NM_001035221 NM_012508 NM_012513 NM_012526 NM_012598 NM_012647 NM_012664 NM_012670 NM_012736 NM_012757 NM_012828 NM_012839 NM_012856 NM_012887 NM_012905 NM_012932 NM_012934 NM_012956 NM_012985 NM_013002 NM_013018 NM_013055 NM_013067 NM_013079 NM_013131 NM_013134 NM_013177 NM_013179 NM_013189 NM_013192 NM_013214 NM_013219 NM_013223 NM_017011 NM_017025 NM_017042 NM_017063 NM_017107 NM_017136 NM_017175 NM_017243 NM_017268 NM_017278 NM_017295 NM_017313 NM_017318 NM_017322 NM_017332 NM_017344 NM_017346 NM_017352 NM_017359 NM_019124 NM_019140 NM_019169 NM_019182 NM_019194 NM_019196 NM_019218 NM_019226 NM_019234 NM_019264 NM_019277 NM_019304 NM_019348 NM_019376 NM_019377 NM_021697 NM_021739 NM_021757 NM_021758 NM_021765 NM_021850 NM_022008 NM_022209 NM_022278 NM_022289 NM_022300 NM_022301 NM_022383 NM_022387 NM_022521 NM_022585 NM_022609 NM_022674 NM_022685 NM_022850 NM_022863 NM_022869 NM_022934 NM_022962 NM_023957 NM_023960 NM_023974 NM_023975 NM_023977 NM_023979 NM_024137 NM_024139 NM_024156 NM_024161 NM_024351 NM_024362 NM_024374 NM_024403 NM_024486 NM_030835 NM_031090 NM_031138 NM_031146 NM_031152 NM_031153 NM_031235 NM_031237 NM_031325 NM_031330 NM_031334 NM_031358 NM_031360 NM_031579 NM_031603 NM_031639 NM_031662 NM_031675 NM_031676 NM_031693 NM_031718 NM_031719 NM_031728 NM_031745 NM_031757 NM_031783 NM_031785 NM_031786 NM_031802 NM_031813 NM_031824 NM_031828 NM_031969 NM_031977 NM_031978 NM_031987 NM_032057 NM_032083 NM_032614 NM_052809 NM_053291 NM_053301 NM_053316 NM_053319 NM_053337 NM_053339 NM_053346 NM_053349 NM_053351 NM_053357 NM_053404 NM_053410 NM_053420 NM_053428 NM_053441 NM_053458 NM_053490 NM_053522 NM_053556 NM_053558 NM_053588 NM_053594 NM_053605 NM_053607 NM_053623 NM_053655 NM_053682 NM_053690 NM_053693 NM_053698 NM_053707 NM_053747 NM_053748 NM_053750 NM_053764 NM_053772 NM_053775 NM_053795 NM_053801 NM_053825 NM_053868 NM_053876 NM_053888 NM_053909 NM_053928 NM_053933 NM_053947 NM_053948 NM_053979 NM_054009 NM_057098 NM_057099 NM_057108 NM_057196 NM_080402 NM_080411 NM_080481 NM_080582 NM_080781 NM_080887 NM_080902 NM_130429 NM_130746 NM_130779 NM_131904 NM_133313 NM_133427 NM_133528 NM_133539 NM_133566 NM_134383 NM_134456 NM_138519 NM_138856 NM_138865 NM_138890 NM_138910 NM_138911 NM_139097 NM_139325 NM_144758 NM_145184 NM_145772 NM_145788 NM_147211 NM_153297 NM_153630 NM_171990 NM_172039 NM_172074 NM_172243 NM_172332 NM_173133 NM_173137 NM_173154 NM_173290 NM_173308 NM_175595 NM_177425 NM_177929 NM_181083 NM_181473 NM_181626 NM_182814 NM_182819 NM_183052 NM_183332 NM_184050 NM_198749 NM_198757 NM_198788 NM_199094 NM_199104 NM_199385 NM_199393 NM_199410 NM_201421 NM_207617 NM_212494 NM_212519 NM_212549 NM_213559 X53232 XM_213362 XM_213382 XM_213782 XM_213898 XM_214021 XM_214053 XM_214241 XM_214296 XM_214420 XM_214446 XM_214505 XM_214625 XM_214701 XM_214833 XM_214954 XM_215044 XM_215113 XM_215118 XM_215178 XM_215286 XM_215416 XM_215424 XM_215481 XM_215549 XM_215570 XM_215612 XM_215706 XM_215717 XM_215751 XM_215758 XM_215769 XM_215771 XM_216013 XM_216212 XM_216378 XM_216393 XM_216398 XM_216563 XM_216643 XM_216661 XM_217019 XM_217124 XM_217464 XM_217560 XM_217587 XM_217592 XM_218196 XM_218790 XM_219525 XM_219685 XM_219693 XM_219801 XM_219939 XM_220047 XM_220155 XM_220167 XM_220178 XM_220269 XM_220281 XM_220428 XM_220506 XM_220534 XM_220541 XM_220753 XM_220992 XM_221050 XM_221212 XM_221276 XM_221888 XM_221941 XM_221946 XM_221962 XM_222177 XM_222214 XM_222478 XM_222670 XM_222946 XM_223485 XM_223580 XM_223981 XM_224271 XM_224332 XM_224417 XM_224478 XM_225078 XM_225138 XM_225923 XM_226014 XM_226238 XM_226422 XM_227811 XM_229106 XM_230523 XM_230531 XM_230861 XM_231148 XM_231251 XM_232252 XM_232343 XM_233231 XM_233467 XM_233609 XM_233944 XM_234011 XM_234272 XM_234483 XM_235185 XM_235224 XM_235496 XM_235497 XM_236476 XM_236745 XM_236941 XM_237291 XM_237327 XM_237787 XM_237957 XM_238334 XM_238346 XM_340874 XM_340986 XM_340987 XM_340999 XM_341071 XM_341337 XM_341354 XM_341558 XM_341653 XM_341661 XM_341669 XM_341686 XM_341700 XM_341709 XM_341803 XM_341947 XM_342048 XM_342101 XM_342149 XM_342174 XM_342180 XM_342217 XM_342223 XM_342340 XM_342442 XM_342489 XM_342534 XM_342551 XM_342581 XM_342600 XM_342632 XM_342657 XM_342829 XM_342851 XM_342857 XM_342924 XM_343018 XM_343154 XM_343175 XM_343175 XM_343459 XM_343469 XM_343557 XM_343579 XM_344130 XM_344450 XM_344706 XM_344971 XM_345150 XM_345266 XM_345938 XM_573165 XM_573256 XM_574503 XM_574916 XM_574979 XM_574991 XM_576252 XM_578542

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 37

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 37 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 37 CA3 - AU ANOVA POSITIVE CORRELATION GENBANK ® ID AW525560 BF562800 M59859 NM_001002277 NM_001003401 NM_001004082 NM_001004220 NM_001005761 NM_001005889 NM_001006957 NM_001007616 NM_001008335 NM_001008368 NM_001008879 NM_001009692 NM_001009825 NM_001011915 NM_001012064 NM_001012157 NM_001012183 NM_001012504 NM_001017960 NM_001024371 NM_001024790 NM_001024906 NM_001029897 NM_001033961 NM_001034020 NM_001034131 NM_001034924 NM_012504 NM_012518 NM_012673 NM_012734 NM_012809 NM_012836 NM_012877 NM_012886 NM_013038 NM_013066 NM_013126 NM_013135 NM_013181 NM_017155 NM_017190 NM_017211 NM_017242 NM_017288 NM_017290 NM_017294 NM_017304 NM_017327 NM_019128 NM_019148 NM_019288 NM_019375 NM_020075 NM_020088 NM_021597 NM_021659 NM_021748 NM_021767 NM_021775 NM_022206 NM_022254 NM_022533 NM_022589 NM_022668 NM_022690 NM_022703 NM_022946 NM_023020 NM_024397 NM_030862 NM_030990 NM_031036 NM_031037 NM_031066 NM_031117 NM_031150 NM_031515 NM_031608 NM_031613 NM_031690 NM_031707 NM_031715 NM_031730 NM_031743 NM_032617 NM_053311 NM_053335 NM_053358 NM_053391 NM_053457 NM_053589 NM_053664 NM_053777 NM_053818 NM_053859 NM_053878 NM_053910 NM_053980 NM_054003 NM_057139 NM_057140 NM_057201 NM_080482 NM_080904 NM_133395 NM_133405 NM_133567 NM_133568 NM_134413 NM_138502 NM_138896 NM_138907 NM_139060 NM_144756 NM_145091 NM_145094 NM_148891 NM_153317 NM_172023 NM_173120 NM_175708 NM_175761 NM_181087 NM_181634 NM_184049 NM_199372 XM_213824 XM_214031 XM_214172 XM_214253 XM_214740 XM_214775 XM_215182 XM_215919 XM_216739 XM_217021 XM_217059 XM_217279 XM_217432 XM_218226 XM_218704 XM_220420 XM_220423 XM_221672 XM_222245 XM_224538 XM_224713 XM_226076 XM_227510 XM_231121 XM_232345 XM_232351 XM_232946 XM_232987 XM_233767 XM_233798 XM_234901 XM_234908 XM_235179 XM_235639 XM_236268 XM_237790 XM_238072 XM_238336 XM_239329 XM_240330 XM_241981 XM_340912 XM_341081 XM_341201 XM_341341 XM_341352 XM_341548 XM_341789 XM_341857 XM_341961 XM_342279 XM_342405 XM_342612 XM_342682 XM_342684 XM_343114 XM_343175 XM_343358 XM_343468 XM_343483 XM_343513 XM_343588 XM_344661 XM_344862 XM_345867

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 38

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 38 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 38 CA3 - AU ANOVA NEGATIVE CORRELATION GENBANK ® ID AA956668 AI716912 NM_001002807 NM_001005561 NM_001008773 NM_001008826 NM_001009651 NM_001011983 NM_001014044 NM_001017376 NM_001024274 NM_001025407 NM_012517 NM_012548 NM_013001 NM_013218 NM_017171 NM_019318 NM_019384 NM_020308 NM_022282 NM_022626 NM_022681 NM_022686 NM_031642 NM_031686 NM_031807 NM_031985 NM_033021 NM_053539 NM_053635 NM_053642 NM_053787 NM_053890 NM_080899 NM_133304 NM_134457 NM_138710 NM_138839 NM_138874 NM_138887 NM_139192 NM_181638 NM_199084 XM_213658 XM_214191 XM_214509 XM_214906 XM_215303 XM_215540 XM_215858 XM_215947 XM_216380 XM_218759 XM_219297 XM_222184 XM_224232 XM_228305 XM_228644 XM_230634 XM_230846 XM_232247 XM_232253 XM_233970 XM_234017 XM_234238 XM_236380 XM_238163 XM_342432 XM_343910 XM_344606 XM_345418 XM_347168 XM_573259

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 39

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 39 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 39 CA3 - AU ANOVA INCREASE GENBANK ® ID AI071000 BI285065 NM_001004253 NM_001004273 NM_001005557 NM_001005907 NM_001007666 NM_001007704 NM_001007755 NM_001008293 NM_001008344 NM_001008521 NM_001011894 NM_001011941 NM_001012016 NM_001012021 NM_001012049 NM_001012087 NM_001012128 NM_001012160 NM_001012169 NM_001012174 NM_001012459 NM_001013077 NM_001013137 NM_001013148 NM_001013178 NM_001013193 NM_001013873 NM_001014790 NM_001015027 NM_001017381 NM_001024247 NM_001024275 NM_001025027 NM_001025123 NM_001025693 NM_001025708 NM_001025716 NM_001029909 NM_001031655 NM_001031660 NM_001033699 NM_001033705 NM_001034111 NM_001034164 NM_001034199 NM_012636 NM_012645 NM_012731 NM_012801 NM_012935 NM_012945 NM_012988 NM_013006 NM_013040 NM_013057 NM_016993 NM_017067 NM_017103 NM_017172 NM_017303 NM_017305 NM_019163 NM_019340 NM_019363 NM_022197 NM_022506 NM_022715 NM_022921 NM_024002 NM_024373 NM_024388 NM_024405 NM_024489 NM_030987 NM_030992 NM_031021 NM_031023 NM_031082 NM_031083 NM_031098 NM_031114 NM_031322 NM_031597 NM_031599 NM_031640 NM_031656 NM_031699 NM_031721 NM_031771 NM_031779 NM_031789 NM_031793 NM_031798 NM_053453 NM_053541 NM_053584 NM_053604 NM_053713 NM_053714 NM_053826 NM_053842 NM_053887 NM_053946 NM_053965 NM_053998 NM_057107 NM_057147 NM_130400 NM_130409 NM_130413 NM_133392 NM_133571 NM_133593 NM_133620 NM_134326 NM_134364 NM_134389 NM_138873 NM_138888 NM_139332 NM_139336 NM_145789 NM_172157 NM_173123 NM_181363 NM_181432 NM_182816 NM_182953 NM_183331 NM_199111 NM_199268 NM_199403 NM_201988 NM_207602 XM_213338 XM_213370 XM_213418 XM_213679 XM_214043 XM_214362 XM_214621 XM_216225 XM_216517 XM_216725 XM_217146 XM_217191 XM_217209 XM_217210 XM_217284 XM_219531 XM_220095 XM_220335 XM_220612 XM_220813 XM_221034 XM_221231 XM_221263 XM_221333 XM_222155 XM_222773 XM_223117 XM_223161 XM_223390 XM_223418 XM_223643 XM_223820 XM_224588 XM_224627 XM_224733 XM_225559 XM_225644 XM_225688 XM_225864 XM_226237 XM_226769 XM_226976 XM_227475 XM_227657 XM_231524 XM_232330 XM_232466 XM_232578 XM_233485 XM_233535 XM_233815 XM_234205 XM_234540 XM_234921 XM_234942 XM_235248 XM_236275 XM_236292 XM_236914 XM_237458 XM_237808 XM_238039 XM_238166 XM_341173 XM_341208 XM_341280 XM_341295 XM_341312 XM_341380 XM_341508 XM_341578 XM_341590 XM_341639 XM_341688 XM_342044 XM_342271 XM_342528 XM_342605 XM_342641 XM_342837 XM_343002 XM_343088 XM_343318 XM_343326 XM_343548 XM_343559 XM_344002 XM_345652 XM_347163 XM_575968 XM_576312

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 40

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 40 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 40 CA3 - AU ANOVA DECREASE GENBANK ® ID AW251888 BE111604 BI303536 NM_001004200 NM_001004206 NM_001004233 NM_001004262 NM_001005555 NM_001005560 NM_001005881 NM_001007607 NM_001008364 NM_001008694 NM_001009618 NM_001011925 NM_001011926 NM_001012004 NM_001012065 NM_001012066 NM_001012113 NM_001012175 NM_001013079 NM_001013103 NM_001013231 NM_001024269 NM_001025414 NM_001025649 NM_001025688 NM_001025722 NM_001025770 NM_001031845 NM_001033670 NM_001033681 NM_001033889 NM_001033914 NM_001033968 NM_001034009 NM_001034135 NM_012506 NM_012527 NM_012613 NM_012628 NM_012660 NM_012686 NM_012700 NM_012755 NM_012756 NM_012776 NM_012798 NM_012841 NM_012918 NM_012941 NM_012947 NM_013073 NM_013199 NM_013222 NM_016990 NM_017008 NM_017049 NM_017051 NM_017053 NM_017102 NM_017204 NM_017253 NM_017262 NM_017312 NM_017319 NM_019133 NM_019164 NM_019224 NM_019306 NM_019326 NM_019343 NM_019378 NM_019621 NM_021681 NM_021739 NM_021760 NM_021835 NM_021847 NM_021859 NM_022185 NM_022262 NM_022267 NM_022382 NM_022386 NM_022507 NM_022675 NM_022693 NM_022864 NM_022953 NM_023101 NM_023972 NM_024000 NM_024146 NM_024163 NM_030846 NM_031008 NM_031056 NM_031081 NM_031097 NM_031147 NM_031331 NM_031342 NM_031518 NM_031522 NM_031595 NM_031614 NM_031646 NM_031654 NM_031667 NM_031692 NM_031765 NM_031776 NM_031777 NM_031820 NM_031831 NM_031975 NM_032062 NM_032616 NM_033359 NM_053310 NM_053409 NM_053435 NM_053440 NM_053486 NM_053573 NM_053620 NM_053684 NM_053788 NM_053837 NM_053846 NM_053894 NM_053955 NM_053972 NM_053973 NM_057116 NM_057136 NM_057152 NM_057207 NM_057209 NM_057213 NM_080583 NM_080896 NM_130420 NM_130428 NM_130755 NM_133406 NM_133414 NM_133582 NM_134336 NM_134376 NM_134400 NM_134404 NM_138921 NM_145090 NM_145781 NM_147209 NM_172075 NM_175754 NM_177481 NM_181092 NM_182668 NM_182842 NM_198749 NM_198758 NM_207599 NM_212458 XM_213437 XM_213777 XM_214313 XM_214316 XM_214673 XM_214720 XM_214751 XM_214899 XM_215371 XM_215451 XM_215467 XM_216835 XM_218432 XM_218615 XM_219529 XM_220232 XM_222103 XM_222662 XM_224389 XM_226439 XM_227282 XM_228114 XM_233737 XM_234514 XM_234909 XM_235156 XM_238177 XM_238280 XM_239780 XM_242062 XM_243390 XM_340886 XM_340911 XM_340967 XM_341088 XM_341091 XM_341157 XM_341896 XM_341963 XM_342244 XM_342477 XM_342653 XM_342808 XM_342823 XM_342854 XM_343581 XM_343613 XM_343839 XM_345870 XM_345909 XM_345970 XM_577103 XM_578287

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 41

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 41 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 41 DG - AI ANOVA POSITIVE CORRELATION GENBANK ® ID AA892549 AF023090 AI317821 AI717047 BG662522 BI298090 BM390128 BM391371 NM_001001513 NM_001002815 NM_001002828 NM_001004080 NM_001004081 NM_001004090 NM_001004199 NM_001004209 NM_001004247 NM_001004254 NM_001004255 NM_001004273 NM_001005383 NM_001005539 NM_001005872 NM_001005898 NM_001005902 NM_001006967 NM_001006968 NM_001006987 NM_001006989 NM_001007146 NM_001007616 NM_001007624 NM_001007625 NM_001007654 NM_001007682 NM_001007691 NM_001007712 NM_001008279 NM_001008319 NM_001008324 NM_001008356 NM_001008374 NM_001008509 NM_001009474 NM_001009536 NM_001009625 NM_001009686 NM_001009690 NM_001009693 NM_001009708 NM_001009973 NM_001011891 NM_001011893 NM_001011903 NM_001011906 NM_001011910 NM_001011920 NM_001011946 NM_001011958 NM_001011970 NM_001011974 NM_001012004 NM_001012030 NM_001012050 NM_001012051 NM_001012067 NM_001012083 NM_001012106 NM_001012120 NM_001012159 NM_001012161 NM_001012171 NM_001012180 NM_001012217 NM_001012235 NM_001013034 NM_001013046 NM_001013070 NM_001013082 NM_001013086 NM_001013087 NM_001013105 NM_001013118 NM_001013121 NM_001013167 NM_001013174 NM_001013206 NM_001013231 NM_001013874 NM_001014772 NM_001015005 NM_001024256 NM_001024261 NM_001024746 NM_001024773 NM_001025123 NM_001025130 NM_001025142 NM_001025152 NM_001025625 NM_001025633 NM_001025664 NM_001025678 NM_001025716 NM_001031641 NM_001031644 NM_001033683 NM_001033696 NM_001033699 NM_001033707 NM_001033715 NM_001033852 NM_001033866 NM_001033868 NM_001033926 NM_001033951 NM_001033968 NM_001033987 NM_001034020 NM_001034068 NM_001034090 NM_001034110 NM_001034998 NM_001034999 NM_001035221 NM_012500 NM_012512 NM_012527 NM_012543 NM_012569 NM_012577 NM_012595 NM_012618 NM_012628 NM_012663 NM_012732 NM_012744 NM_012749 NM_012777 NM_012788 NM_012816 NM_012820 NM_012838 NM_012884 NM_012913 NM_012963 NM_012971 NM_012993 NM_013000 NM_013013 NM_013022 NM_013088 NM_013091 NM_013154 NM_013156 NM_013164 NM_013194 NM_013198 NM_013226 NM_016990 NM_017051 NM_017052 NM_017060 NM_017068 NM_017109 NM_017116 NM_017125 NM_017132 NM_017137 NM_017148 NM_017181 NM_017204 NM_017212 NM_017216 NM_017223 NM_017232 NM_017234 NM_017264 NM_017274 NM_017288 NM_017317 NM_017320 NM_017340 NM_017343 NM_019124 NM_019132 NM_019141 NM_019204 NM_019211 NM_019226 NM_019232 NM_019242 NM_019253 NM_019257 NM_019272 NM_019289 NM_019359 NM_019362 NM_020308 NM_021663 NM_021694 NM_021703 NM_021746 NM_021748 NM_021766 NM_021847 NM_021859 NM_021863 NM_022207 NM_022226 NM_022265 NM_022281 NM_022286 NM_022382 NM_022390 NM_022499 NM_022500 NM_022502 NM_022523 NM_022526 NM_022538 NM_022592 NM_022595 NM_022596 NM_022597 NM_022601 NM_022617 NM_022699 NM_022701 NM_022799 NM_022853 NM_022939 NM_023972 NM_023978 NM_024155 NM_024359 NM_024374 NM_024399 NM_024404 NM_030826 NM_030992 NM_031022 NM_031035 NM_031057 NM_031099 NM_031114 NM_031120 NM_031147 NM_031149 NM_031357 NM_031509 NM_031525 NM_031553 NM_031554 NM_031589 NM_031596 NM_031632 NM_031654 NM_031657 NM_031664 NM_031683 NM_031711 NM_031729 NM_031745 NM_031752 NM_031770 NM_031774 NM_031786 NM_031789 NM_031812 NM_031816 NM_031827 NM_031830 NM_031837 NM_031970 NM_031981 NM_032067 NM_032416 NM_032619 NM_053323 NM_053401 NM_053411 NM_053448 NM_053462 NM_053467 NM_053507 NM_053538 NM_053555 NM_053598 NM_053599 NM_053600 NM_053604 NM_053665 NM_053698 NM_053750 NM_053776 NM_053777 NM_053794 NM_053804 NM_053851 NM_053870 NM_053886 NM_053911 NM_053927 NM_053936 NM_053959 NM_053985 NM_054001 NM_057100 NM_057114 NM_057118 NM_057131 NM_057192 NM_057197 NM_057204 NM_057208 NM_057210 NM_080480 NM_080577 NM_080691 NM_080767 NM_080773 NM_080888 NM_080910 NM_130409 NM_130416 NM_133398 NM_133401 NM_133404 NM_133421 NM_133551 NM_133585 NM_134376 NM_134390 NM_134410 NM_134415 NM_134449 NM_134456 NM_134468 NM_138508 NM_138877 NM_138889 NM_138896 NM_138917 NM_139107 NM_139110 NM_139256 NM_139325 NM_139329 NM_147177 NM_147210 NM_153469 NM_153628 NM_153630 NM_172009 NM_172033 NM_172334 NM_173116 NM_175578 NM_175582 NM_175765 NM_177927 NM_181388 NM_181475 NM_182953 NM_183328 NM_183402 NM_198787 NM_199087 NM_199108 NM_199118 NM_199119 NM_199384 NM_199388 NM_199408 NM_206847 NM_207591 NM_207599 NM_212463 NM_212491 NM_212509 XM_213329 XM_213342 XM_213463 XM_213673 XM_213677 XM_213729 XM_213739 XM_213824 XM_213832 XM_213972 XM_213993 XM_214147 XM_214172 XM_214279 XM_214518 XM_214843 XM_214859 XM_214963 XM_214968 XM_215028 XM_215101 XM_215113 XM_215177 XM_215222 XM_215285 XM_215674 XM_215733 XM_215754 XM_215935 XM_215939 XM_216124 XM_216230 XM_216306 XM_216386 XM_216407 XM_216515 XM_216565 XM_216629 XM_216704 XM_216740 XM_216835 XM_216872 XM_216968 XM_217061 XM_217195 XM_217478 XM_217740 XM_218336 XM_218816 XM_218858 XM_219001 XM_219515 XM_219885 XM_219948 XM_220512 XM_220574 XM_220775 XM_221297 XM_221747 XM_222661 XM_223012 XM_223125 XM_223597 XM_223938 XM_224232 XM_224630 XM_224788 XM_225014 XM_225259 XM_225457 XM_225726 XM_226237 XM_226987 XM_227074 XM_228044 XM_228701 XM_230291 XM_230637 XM_231162 XM_232323 XM_232745 XM_232855 XM_233415 XM_233761 XM_233798 XM_234008 XM_234205 XM_234394 XM_235400 XM_235426 XM_235518 XM_235657 XM_236189 XM_236192 XM_236362 XM_236468 XM_236659 XM_236687 XM_237415 XM_237787 XM_238019 XM_238155 XM_241632 XM_242032 XM_243652 XM_340798 XM_340818 XM_340825 XM_340997 XM_341051 XM_341052 XM_341086 XM_341157 XM_341704 XM_341785 XM_341790 XM_341796 XM_341799 XM_341826 XM_341867 XM_341882 XM_341934 XM_341940 XM_341957 XM_342002 XM_342409 XM_342542 XM_342866 XM_342918 XM_343119 XM_343157 XM_343268 XM_343336 XM_343396 XM_343564 XM_343570 XM_343773 XM_343776 XM_343986 XM_344286 XM_344403 XM_344409 XM_344870 XM_344970 XM_345477 XM_345535 XM_345870 XM_346083 XM_573258 XM_574670 XM_577023

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 42

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 42 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 42 DG - AI ANOVA NEGATIVE CORRELATION GENBANK ® ID BF557865 BM391206 NM_001004102 NM_001009689 NM_001013071 NM_001024238 NM_013111 NM_024355 NM_031123 NM_031127 NM_053775 NM_134383 NM_173094 NM_212504 XM_218939 XM_219292 XM_219879 XM_221074 XM_223729 XM_224733 XM_230288 XM_231453 XM_234508 XM_343446 XM_344594 XM_345938

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 43

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 43 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 43 DG - AI ANOVA INCREASE GENBANK ® ID AI103331 AI235284 AW526364 BI291997 NM_001001511 NM_001001516 NM_001002016 NM_001002802 NM_001002835 NM_001004076 NM_001004099 NM_001004218 NM_001004245 NM_001005528 NM_001005529 NM_001005893 NM_001005907 NM_001006971 NM_001007001 NM_001007557 NM_001007677 NM_001007684 NM_001007749 NM_001007755 NM_001007802 NM_001008315 NM_001008725 NM_001008767 NM_001008768 NM_001008829 NM_001009172 NM_001009502 NM_001009623 NM_001009668 NM_001009669 NM_001009683 NM_001011919 NM_001011985 NM_001012147 NM_001012190 NM_001012464 NM_001013047 NM_001013059 NM_001013072 NM_001013081 NM_001013135 NM_001013179 NM_001013193 NM_001013204 NM_001013207 NM_001013210 NM_001013233 NM_001013246 NM_001015026 NM_001017382 NM_001024268 NM_001024771 NM_001024775 NM_001024782 NM_001025423 NM_001025630 NM_001025721 NM_001030026 NM_001030041 NM_001033653 NM_001033656 NM_001033757 NM_001034004 NM_001034164 NM_012515 NM_012523 NM_012532 NM_012546 NM_012562 NM_012576 NM_012578 NM_012614 NM_012650 NM_012701 NM_012703 NM_012722 NM_012740 NM_012771 NM_012856 NM_012862 NM_012886 NM_012925 NM_012940 NM_012974 NM_013015 NM_013070 NM_013104 NM_013107 NM_013122 NM_013135 NM_013137 NM_013146 NM_017009 NM_017024 NM_017037 NM_017043 NM_017062 NM_017139 NM_017142 NM_017200 NM_017224 NM_017262 NM_017351 NM_019143 NM_019144 NM_019219 NM_019249 NM_019266 NM_019312 NM_019313 NM_019318 NM_019335 NM_019346 NM_019386 NM_019904 NM_019905 NM_020082 NM_020088 NM_021578 NM_021582 NM_021690 NM_021769 NM_021771 NM_021989 NM_022215 NM_022244 NM_022251 NM_022257 NM_022266 NM_022270 NM_022285 NM_022401 NM_022504 NM_022516 NM_022531 NM_022677 NM_022692 NM_022866 NM_024129 NM_024131 NM_024133 NM_024353 NM_024358 NM_024369 NM_024372 NM_024400 NM_030843 NM_030847 NM_030863 NM_030872 NM_030987 NM_031018 NM_031031 NM_031118 NM_031140 NM_031145 NM_031242 NM_031320 NM_031332 NM_031511 NM_031514 NM_031549 NM_031560 NM_031630 NM_031728 NM_031739 NM_031797 NM_031814 NM_031818 NM_052804 NM_053356 NM_053455 NM_053485 NM_053503 NM_053536 NM_053554 NM_053560 NM_053570 NM_053583 NM_053612 NM_053618 NM_053654 NM_053670 NM_053684 NM_053796 NM_053838 NM_053857 NM_053882 NM_053896 NM_053933 NM_053936 NM_053992 NM_057107 NM_057200 NM_057211 NM_080479 NM_080584 NM_080698 NM_080899 NM_131911 NM_133296 NM_133298 NM_133305 NM_133307 NM_133317 NM_133522 NM_133526 NM_133548 NM_133598 NM_133605 NM_133624 NM_134419 NM_138502 NM_138521 NM_138542 NM_139185 NM_139216 NM_139255 NM_144757 NM_145091 NM_147205 NM_147206 NM_172022 NM_172029 NM_173118 NM_173145 NM_175579 NM_175756 NM_181087 NM_181368 NM_181377 NM_183330 NM_184051 NM_198786 NM_199093 NM_199208 NM_199270 NM_206849 NM_207596 NM_207598 NM_207609 NM_212466 NM_212505 NM_212523 NM_212525 NM_212547 XM_213408 XM_213421 XM_213460 XM_213526 XM_213611 XM_214344 XM_214441 XM_214526 XM_214583 XM_214673 XM_214721 XM_214769 XM_214935 XM_214993 XM_215076 XM_215095 XM_215117 XM_215372 XM_215376 XM_215424 XM_215576 XM_215578 XM_216018 XM_216688 XM_218368 XM_218963 XM_218977 XM_219045 XM_219470 XM_219966 XM_220333 XM_220398 XM_220644 XM_220810 XM_220982 XM_221272 XM_221380 XM_221387 XM_221916 XM_222636 XM_223583 XM_223781 XM_224296 XM_224538 XM_224561 XM_225196 XM_225548 XM_225625 XM_225631 XM_225644 XM_225997 XM_226016 XM_226213 XM_227066 XM_228197 XM_230036 XM_230462 XM_230647 XM_231134 XM_231402 XM_232283 XM_232622 XM_233779 XM_235024 XM_235049 XM_235710 XM_236458 XM_236560 XM_237371 XM_237754 XM_237792 XM_238447 XM_240178 XM_240311 XM_242644 XM_242982 XM_243637 XM_243815 XM_340939 XM_341227 XM_341448 XM_341509 XM_341540 XM_341584 XM_341784 XM_341857 XM_341877 XM_341880 XM_342072 XM_342092 XM_342271 XM_342284 XM_342317 XM_342432 XM_342759 XM_342829 XM_342905 XM_342979 XM_343058 XM_343065 XM_343126 XM_343259 XM_343334 XM_343479 XM_343619 XM_344421 XM_344524 XM_345584 XM_345702 XM_345789 XM_345825 XM_573544 XM_573983 XM_574161 XM_574618 XM_575585 XM_576363 XM_576401 XM_580221

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 44

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AI ANOVA” was performed, where Aged Unimpaired were combined with Young and compared to Aged Impaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 44 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 44 DG - AI ANOVA DECREASE GENBANK ® ID NM_001005530 NM_001005885 NM_001006994 NM_001007000 NM_001007607 NM_001008353 NM_001008553 NM_001009719 NM_001010965 NM_001011942 NM_001012144 NM_001013209 NM_001017376 NM_001024964 NM_001025136 NM_001025400 NM_001031645 NM_001033684 NM_012585 NM_012934 NM_013066 NM_017030 NM_017093 NM_017197 NM_017259 NM_017290 NM_017318 NM_017357 NM_019264 NM_020097 NM_021597 NM_021702 NM_021760 NM_022615 NM_022688 NM_024364 NM_031082 NM_031318 NM_031571 NM_031613 NM_053301 NM_053340 NM_053360 NM_053441 NM_053883 NM_080397 NM_133315 NM_133387 NM_133562 NM_144758 NM_172034 NM_173325 NM_199081 XM_214701 XM_215134 XM_215883 XM_216477 XM_217115 XM_219723 XM_220607 XM_221888 XM_221941 XM_221962 XM_222223 XM_222460 XM_222662 XM_224474 XM_224947 XM_226624 XM_233260 XM_233490 XM_233679 XM_234470 XM_236614 XM_237307 XM_239171 XM_340856 XM_340999 XM_341241 XM_341709 XM_341983 XM_342107 XM_343817 XM_343919 XM_347168 XM_575397

The genes in this set show abundance of expressed gene product(s) in the Aged Impaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Unimpaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 45

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 45 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 45 DG - AU ANOVA POSITIVE CORRELATION GENBANK ® ID AI501759 BE329232 NM_001003975 NM_001004253 NM_001004269 NM_001004275 NM_001005381 NM_001005876 NM_001006960 NM_001006963 NM_001006981 NM_001007020 NM_001007620 NM_001007714 NM_001007731 NM_001007744 NM_001008277 NM_001008291 NM_001008298 NM_001008338 NM_001008352 NM_001008508 NM_001008556 NM_001008766 NM_001008839 NM_001008891 NM_001009602 NM_001009619 NM_001009637 NM_001009657 NM_001009825 NM_001011964 NM_001011975 NM_001011983 NM_001012138 NM_001012208 NM_001012504 NM_001013114 NM_001013245 NM_001017385 NM_001017386 NM_001024745 NM_001024756 NM_001024785 NM_001024874 NM_001025409 NM_001025660 NM_001025688 NM_001025695 NM_001025735 NM_001025748 NM_001030023 NM_001031648 NM_001031653 NM_001031659 NM_001033065 NM_001033079 NM_001033670 NM_001033702 NM_001033870 NM_001034009 NM_001034026 NM_001034129 NM_001034834 NM_012615 NM_012809 NM_012836 NM_012991 NM_012998 NM_013053 NM_013192 NM_017029 NM_017040 NM_017075 NM_017190 NM_017201 NM_019133 NM_019271 NM_019352 NM_019379 NM_020099 NM_021262 NM_021697 NM_021770 NM_021835 NM_021869 NM_022198 NM_022282 NM_022296 NM_022498 NM_023971 NM_024147 NM_030989 NM_031028 NM_031125 NM_031137 NM_031139 NM_031152 NM_031515 NM_031521 NM_031528 NM_031600 NM_031641 NM_031646 NM_031768 NM_031783 NM_031979 NM_032066 NM_053291 NM_053404 NM_053440 NM_053457 NM_053508 NM_053561 NM_053620 NM_053770 NM_053779 NM_053811 NM_053818 NM_053842 NM_053850 NM_053874 NM_053928 NM_053965 NM_053999 NM_054004 NM_054006 NM_057132 NM_057141 NM_080478 NM_080887 NM_080895 NM_130406 NM_130826 NM_130894 NM_133310 NM_133569 NM_133582 NM_133594 NM_133615 NM_138528 NM_138840 NM_138899 NM_138900 NM_139109 NM_139186 NM_139194 NM_139254 NM_144754 NM_145085 NM_145878 NM_152935 NM_153297 NM_171994 NM_172157 NM_173115 NM_173290 NM_175595 NM_175603 NM_175838 NM_181081 NM_182671 NM_182820 NM_183332 NM_184049 NM_198771 NM_198789 NM_199372 NM_199380 NM_199500 XM_213382 XM_213437 XM_213569 XM_214155 XM_214238 XM_214420 XM_214570 XM_214625 XM_214817 XM_215659 XM_215701 XM_215847 XM_215985 XM_216041 XM_216169 XM_216198 XM_216367 XM_216400 XM_216524 XM_216801 XM_217124 XM_217592 XM_217806 XM_218720 XM_218949 XM_219693 XM_220884 XM_220982 XM_221100 XM_223227 XM_223837 XM_224169 XM_224429 XM_225468 XM_225711 XM_225983 XM_232315 XM_233231 XM_235552 XM_235640 XM_237999 XM_238205 XM_238280 XM_238380 XM_240330 XM_340750 XM_340775 XM_341058 XM_341120 XM_341653 XM_341666 XM_341714 XM_341856 XM_341878 XM_341961 XM_342004 XM_342286 XM_342300 XM_342489 XM_342521 XM_342532 XM_342632 XM_342872 XM_343006 XM_343034 XM_343117 XM_343175 XM_343459 XM_343513 XM_343922 XM_344113 XM_347236 XM_577103

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals positively correlate with learning index of the animals, such that poorer learners have higher abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

Example 46

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Pearson's correlations comparing probe set signal values to learning indices were then calculated for the aged animals (excluding young) across all present probe sets. Again, correlations representing a p-value of less than 0.05 were considered significantly changed.

Microarray Results

Table 46 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 46 DG - AU ANOVA NEGATIVE CORRELATION GENBANK ® ID BF411876 NM_001008511 NM_001012093 NM_001013090 NM_001024258 NM_001024865 NM_001034994 NM_013159 NM_022202 NM_022236 NM_022518 NM_031635 NM_031698 NM_053416 NM_053621 NM_133593 NM_134326 NM_172039 NM_181362 NM_212498 XM_214253 XM_215942 XM_215947 XM_215990 XM_220222 XM_220813 XM_221043 XM_226666 XM_233808 XM_341215 XM_342580 XM_344785

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. In addition, the abundance of expressed gene product(s) in the aged animals negatively correlate with learning index of the animals, such that poorer learners have lower abundances of expressed gene products of the selected genes. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 47

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 47 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 47 DG - AU ANOVA INCREASE GENBANK ® ID NM_001002831 NM_001005888 NM_001007680 NM_001007704 NM_001012092 NM_001012195 NM_001013120 NM_001024767 NM_001025125 NM_001025722 NM_001033701 NM_012853 NM_012935 NM_012959 NM_013126 NM_016994 NM_019170 NM_021688 NM_022269 NM_022525 NM_022684 NM_023095 NM_023977 NM_024378 NM_031569 NM_031610 NM_031742 NM_031751 NM_040669 NM_052807 NM_053355 NM_053442 NM_053644 NM_053826 NM_057196 NM_080897 NM_133302 NM_133558 NM_138922 NM_153740 NM_172327 NM_213562 XM_213921 XM_214730 XM_214906 XM_215742 XM_215949 XM_215984 XM_217246 XM_217293 XM_217837 XM_218293 XM_218432 XM_221037 XM_222155 XM_224720 XM_225168 XM_225253 XM_226315 XM_226976 XM_231143 XM_232253 XM_232735 XM_233421 XM_234238 XM_235986 XM_340785 XM_340879 XM_340935 XM_341590 XM_343146 XM_344785 XM_577078

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly increased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should increase the abundance or enhance the function of the expressed gene products of these genes.

Example 48

An ANOVA was conducted on the probe set signal values for all probe sets by combining two groups of animals and comparing them to the third group. An “AU ANOVA” was performed, where Aged Impaired were combined with Young and compared to Aged Unimpaired. All probe sets were considered in the statistical analysis based on the gcRMA method of data extraction from the perfect match sequences for each probe. Any probe sets having a p-value less than 0.05 were considered significantly changed and the genes or plurality of genes selected.

Microarray Results

Table 48 shows the genes that were identified as being associated with cognitive impairment in this experiment. The reference sequence transcript ID (GENBANK® number for the exemplar sequence) was used to identify genes considered significantly changed. When this exemplar ID was not available, a UniGene identifier was used in conjunction with the GENBANK® accession number.

TABLE 48 DG - AU ANOVA DECREASE GENBANK ® ID AI454679 AW142720 AW524426 BE098467 BF282715 NM_001001510 NM_001001719 NM_001001799 NM_001004094 NM_001004132 NM_001004238 NM_001004274 NM_001005547 NM_001007637 NM_001007721 NM_001008301 NM_001008368 NM_001008558 NM_001009631 NM_001009641 NM_001009713 NM_001010953 NM_001010961 NM_001011896 NM_001011904 NM_001011956 NM_001011978 NM_001011987 NM_001012113 NM_001012152 NM_001012175 NM_001013103 NM_001013199 NM_001017537 NM_001024747 NM_001024784 NM_001024906 NM_001025421 NM_001025753 NM_001033066 NM_001033693 NM_001034131 NM_001034198 NM_012520 NM_012533 NM_012567 NM_012582 NM_012651 NM_012656 NM_012755 NM_012756 NM_012762 NM_012775 NM_012798 NM_012829 NM_012952 NM_012968 NM_013029 NM_013080 NM_013100 NM_013106 NM_013199 NM_016991 NM_017031 NM_017033 NM_017066 NM_017195 NM_017207 NM_017213 NM_017261 NM_017305 NM_017359 NM_019129 NM_019193 NM_019306 NM_019356 NM_021577 NM_021751 NM_021763 NM_021851 NM_022193 NM_022197 NM_022209 NM_022217 NM_022249 NM_022278 NM_022288 NM_022548 NM_022589 NM_022600 NM_022675 NM_022681 NM_022858 NM_022863 NM_022936 NM_022951 NM_024000 NM_024146 NM_024158 NM_024383 NM_030836 NM_030861 NM_030862 NM_030868 NM_031007 NM_031030 NM_031034 NM_031063 NM_031132 NM_031333 NM_031351 NM_031518 NM_031594 NM_031692 NM_031701 NM_031707 NM_031831 NM_031855 NM_032613 NM_032616 NM_033359 NM_053363 NM_053375 NM_053428 NM_053438 NM_053506 NM_053601 NM_053655 NM_053854 NM_053866 NM_053973 NM_057201 NM_057205 NM_131906 NM_131907 NM_131914 NM_133560 NM_133600 NM_134336 NM_134346 NM_134367 NM_139060 NM_139113 NM_139324 NM_173126 NM_173154 NM_175758 NM_175761 NM_182842 NM_198749 NM_198764 NM_199099 NM_199256 NM_199382 NM_206950 NM_212521 NM_212532 NM_214457 XM_213433 XM_213777 XM_213779 XM_214030 XM_214400 XM_214451 XM_214522 XM_214751 XM_214775 XM_215389 XM_215416 XM_215612 XM_216047 XM_216563 XM_216725 XM_216755 XM_216784 XM_216859 XM_216964 XM_217078 XM_217367 XM_217464 XM_217732 XM_218382 XM_219374 XM_220224 XM_220753 XM_221120 XM_221369 XM_221566 XM_222568 XM_222578 XM_222868 XM_223496 XM_224350 XM_224417 XM_224732 XM_225923 XM_226014 XM_230495 XM_231148 XM_231655 XM_232640 XM_232809 XM_232941 XM_233297 XM_233955 XM_233970 XM_234156 XM_234328 XM_235164 XM_235179 XM_235338 XM_236992 XM_237179 XM_237790 XM_238127 XM_238151 XM_238177 XM_243623 XM_340884 XM_341354 XM_341612 XM_342149 XM_342174 XM_342281 XM_342396 XM_342503 XM_342533 XM_342692 XM_342900 XM_343081 XM_343114 XM_343546 XM_343588 XM_343764 XM_344135 XM_344405 XM_345867 XM_573442 XM_574644

The genes in this set show abundance of expressed gene product(s) in the Aged Unimpaired population that are significantly decreased, as determined by ANOVA, compared to those abundances in Young and Aged Impaired populations combined. Therefore, compounds useful in treating cognitive impairment selected using these genes should decrease the abundance or attenuate the function of the expressed gene products of these genes.

While this invention has been particularly shown and described with references to preferred elements thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims. 

1. A method of identifying a gene or a plurality of genes associated with cognitive impairment in a mammal comprising the steps of: (a) providing an AI population of aged mammals with cognitive impairment; (b) providing an AU population of aged mammals without cognitive impairment; (c) providing a Y population of young mammals; (d) determining the abundance of a plurality of expressed gene products in one or more of the CA1, CA3, and DG hippocampal tissue of each mammal in the AI, AU and Y populations; and (e) selecting a gene or a plurality of genes based on a significant increase or decrease in the relative abundance of the gene's expressed gene product in the AI population of mammals relative to the combined AU and Y populations or in the AU population of mammals relative to the combined AI and Y populations.
 2. A method of identifying a gene or a plurality of genes associated with cognitive impairment in a mammal comprising the steps of: (a) providing an AI population of aged mammals with cognitive impairment; (b) providing an AU population of aged mammals without cognitive impairment; (c) providing a Y population of young mammals; (d) determining the abundance of a plurality of expressed gene products in one or more of the CA1, CA3, and DG hippocampal tissue of each mammal in the AI, AU and Y populations; (e) selecting a gene or a plurality of genes based on a significant increase or decrease in the relative abundance of the gene's expressed gene product in the AI population of mammals relative to the combined AU and Y populations or in the AU population of mammals relative to the combined AI and Y populations; (f) correlating the increased or decreased abundance of a selected gene's expressed gene products with the level of cognitive impairment in each mammal of the AU and AI populations; and (g) selecting a gene or a plurality of genes based on a significant correlation between the relative abundance of the gene's expressed gene product and the level of cognitive impairment in the mammals.
 3. The method according to claim 1 or 2, wherein the significance of the increase or decrease in the relative abundance is determined using a parametric test.
 4. The method according to claim 3, wherein the parametric test is an analysis of variance (ANOVA).
 5. The method according to claim 1 or 2, wherein the significance of the increase or decrease in relative abundance is determined using a non-parametric test.
 6. The method according to claim 5, wherein the non-parametric test is selected from the group consisting of a Mann-Whitney U test, a Wilcoxon rank-sum test, a Wilcoxon matched pairs signed-rank test, a Mann-Whitney-Wilcoxon test, a Kruskal-Wallis analysis of variance by ranks, a Friedman two way analysis of variance, and a Kolmogorov-Smirnov test.
 7. The method according to claim 2, wherein the significance of the correlation is determined using a parametric Pearson correlation coefficient.
 8. The method according to claim 2, wherein the significance of the correlation is determined using a nonparametric Spearman rank correlation coefficient.
 9. The method according to claim 1 or 2, wherein the abundance of the plurality of expressed gene products is determined by a method selected from the group consisting of microarray analysis, macroarray analysis, in situ hybridization histochemistry, fluorescent in situ hybridization (FISH), immunocytochemistry (ICC), enzyme linked immunosorbent assay (ELISA), immunoprecipitation, quantitative polymerase chain reaction (PCR), serial analysis of gene expression (SAGE) analysis, radioimmunoassay (RIA) and blot analysis.
 10. The method according to any one of claims 1 to 9, wherein the mammal is an outbred strain of rat.
 11. The method according to any one of claims 1 to 10, wherein the expressed gene products are RNAs.
 12. The method according to any one of claims 1 to 11, wherein the expressed gene products are proteins, polypeptides or peptides.
 13. A method of identifying a compound useful in the treatment of cognitive impairment comprising the steps of: (a) determining the abundance or function of an expressed gene product in a mammalian cell of the mammalian cell's homologue of a gene or a plurality of genes identified by the method of claim 1 or 2 to increase in abundance in the AI population relative to the combined AU and Y populations or to decrease in abundance in the AU population relative to the combined AI and Y populations or of a gene or genes selected from the group consisting of each of the individual genes listed in Tables 1, 3, 5, 8, 9, 11, 13, 16, 17, 19, 21, 24, 25, 27, 29, 32, 33, 35, 37, 40, 41, 43, 45 and 48 in the presence or absence of a candidate compound; and (b) identifying a compound from any of the candidate compound(s) that significantly decreases that abundance or attenuates the function of that gene or its expressed gene product in the mammalian cell to which the candidate compound is administered.
 14. A method of identifying a compound useful in the treatment of cognitive impairment comprising the steps of: (a) determining the abundance or function of an expressed gene product in a mammalian cell of the mammalian cell's homologue of a gene or a plurality of genes identified by the method of claim 1 or 2 to decrease in abundance in the AI population relative to the combined AU and Y populations or to increase in abundance in the AU population relative to the combined AI and Y populations or of a gene or genes selected from the group consisting of each of the individual genes listed in Tables 2, 4, 6, 7, 10, 12, 14, 15, 18, 20, 22, 23, 26, 28, 30, 31, 34, 36, 38, 39, 42, 44, 46 and 47 in the presence or absence of a candidate compound; and (b) identifying a compound from any of the candidate compound(s) that significantly increases that abundance or enhances the function of that gene or its expressed gene product in the mammalian cell to which the candidate compound is administered.
 15. The method according to claim 13 or 14, wherein the mammalian cell is selected from the group consisting of a neuronal cell and a glial cell.
 16. The method according to claim 15, wherein the mammalian cell is a hippocampal cell.
 17. The method according to claim 16, wherein the hippocampal cell is selected from the group of a CA1 cell, a CA3 cell or a DG cell.
 18. A method of identifying a compound useful in the treatment of cognitive impairment comprising: (a) determining the abundance or function of an expressed gene product, in the hippocampus of a mammal, of the mammal's homologue of a gene or a plurality of genes identified by the method of claim 1 or 2 to increase in abundance in the AI population relative to the combined AU and Y populations or to decrease in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 1, 3, 5, 8, 9, 11, 13, 16, 17, 19, 21, 24, 25, 27, 29, 32, 33, 35, 37, 40, 41, 43, 45 and 48 in the presence or absence of a candidate compound; and (b) identifying a compound from any of the candidate compound(s) that significantly decreases that abundance or attenuates the function of that gene or its expressed gene product in the mammal to whom the candidate compound is administered.
 19. A method of identifying a compound useful in the treatment of cognitive impairment comprising: (a) determining the abundance or function of an expressed gene product, in the hippocampus of a mammal, of the mammal's homologue of a gene or a plurality of genes identified by the method of claim 1 or 2 to decrease in abundance in the AI population relative to the combined AU and Y populations or to increase in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 2, 4, 6, 7, 10, 12, 14, 15, 18, 20, 22, 23, 26, 28, 30, 31, 34, 36, 38, 39, 42, 44, 46 and 47 in the presence or absence of a candidate compound; and (b) identifying a compound from any of the candidate compound(s) that significantly increases that abundance or enhances the function of that gene or its expressed gene product in the mammal to whom the candidate compound is administered.
 20. The method according to claim 18 or 19, wherein the mammal is an aged mammal.
 21. The method according to claim 20, wherein the aged mammal is cognitively impaired.
 22. A method of identifying a compound useful in the treatment of cognitive impairment in aging comprising: (a) determining the abundance or function of an expressed gene product, in the hippocampus of an aged mammal with cognitive impairment, of the mammal's homologue of a gene or a plurality of genes identified by the method of claim 1 or 2 to increase in abundance in the AI population relative to the combined AU and Y populations or to decrease in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 1, 3, 5, 8, 9, 11, 13, 16, 17, 19, 21, 24, 25, 27, 29, 32, 33, 35, 37, 40, 41, 43, 45 and 48 in the presence or absence of a candidate compound; and (b) identifying a compound from among the candidate compound(s) that significantly decreases that abundance or attenuates the function of that gene or its expressed gene product in the aged mammal with cognitive impairment to whom the compound is administered relative to a member of the group consisting of an aged mammal without cognitive impairment, a young mammal, an aged cognitively impaired mammal in the absence of the compound, and two or more of them.
 23. A method of identifying a compound useful in the treatment of cognitive impairment in aging comprising: (a) determining the abundance or function of an expressed gene product, in the hippocampus of an aged mammal with cognitive impairment, of the mammal's homologue of a gene or a plurality of genes identified by the method of claim 1 or 2 to decrease in abundance in the AI population relative to the combined AU and Y populations or to increase in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 2, 4, 6, 7, 10, 12, 14, 15, 18, 20, 22, 23, 26, 28, 30, 31, 34, 36, 38, 39, 42, 44, 46 and 47 in the presence or absence of a candidate compound; and (b) identifying a compound from among the candidate compound(s) that significantly increases that abundance or enhances the function of that gene or its expressed gene product in the aged mammal with cognitive impairment to whom the compound is administered relative to a member of the group consisting of an aged mammal without cognitive impairment, a young mammal, an aged cognitively impaired mammal in the absence of the compound, and two or more of them.
 24. The method according to claim 22 or 23, wherein the compound does not significantly alter that abundance or function in a member of the group consisting of a young mammal, an aged cognitively unimpaired mammal and both, to whom the candidate compound is administered.
 25. A method of identifying a compound useful in the treatment of cognitive impairment comprising: (a) determining the cognitive status of a mammal in the presence or absence of a candidate compound believed to decrease the abundance or attenuate the function of an expressed gene product of a gene or a plurality of genes identified by the method of claim 1 or 2 to increase in abundance in the AI population relative to the combined AU and Y populations or to decrease in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 1, 3, 5, 8, 9, 11, 13, 16, 17, 19, 21, 24, 25, 27, 29, 32, 33, 35, 37, 40, 41, 43, 45 and 48; and (b) identifying the compound from among the candidate compound(s) that beneficially alters the cognitive status of the mammal to whom the compound is administered.
 26. A method of identifying a compound useful in the treatment of cognitive impairment comprising: (a) determining the cognitive status of a mammal in the presence or absence of a candidate compound believed to increase the abundance or enhance the function of an expressed gene product of a gene or a plurality of genes identified by the method of claim 1 or 2 to decrease in abundance in the AI population relative to the combined AU and Y populations or to increase in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 2, 4, 6, 7, 10, 12, 14, 15, 18, 20, 22, 23, 26, 28, 30, 31, 34, 36, 38, 39, 42, 44, 46 and 47; and (b) identifying the compound from among the candidate compound(s) that beneficially alters the cognitive status of the mammal to whom the compound is administered.
 27. The method according to claim 25 or 26, wherein the mammal is an aged mammal.
 28. The method according to claim 27, wherein the aged mammal is cognitively impaired.
 29. A method of identifying a compound useful in the treatment of cognitive impairment in aging comprising: (a) determining the cognitive status of an aged mammal with cognitive impairment, in the presence or absence of a candidate compound believed to decrease the abundance or attenuate the function of an expressed gene product of a gene or a plurality of genes identified by the method of claim 1 or 2 to increase in abundance in the AI population relative to the combined AU and Y populations or to decrease in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 1, 3, 5, 8, 9, 11, 13, 16, 17, 19, 21, 24, 25, 27, 29, 32, 33, 35, 37, 40, 41, 43, 45 and 48; and (b) identifying a compound from among the candidate compound(s) that beneficially alters the cognitive function in the aged mammal with cognitive impairment to whom the compound is administered relative to a member of the group consisting of an aged mammal without cognitive impairment, a young mammal, an aged cognitively impaired mammal to whom the compound is not administered, and two or more of them.
 30. A method of identifying a compound useful in the treatment of cognitive impairment in aging comprising: (a) determining the cognitive status of an aged mammal with cognitive impairment, in the presence or absence of a candidate compound believed to increase the abundance or enhance the function of an expressed gene product of a gene or a plurality of genes identified by the method of claim 1 or 2 to decrease in abundance in the AI population relative to the combined AU and Y populations or to increase in abundance in the AU population relative to the combined AI and Y populations or a gene or genes selected from the group consisting of each of the individual genes listed in Tables 2, 4, 6, 7, 10, 12, 14, 15, 18, 20, 22, 23, 26, 28, 30, 31, 34, 36, 38, 39, 42, 44, 46 and 47; and (b) identifying a compound from among the candidate compound(s) that beneficially alters the cognitive function in the aged mammal with cognitive impairment to whom the compound is administered relative to a member of the group consisting of an aged mammal without cognitive impairment, a young mammal, an aged cognitively impaired mammal to whom the compound is not administered, and two or more of them.
 31. The method according to claim 29 or 30, wherein the compound does not significantly alter the cognitive status of a member of the group consisting of a young mammal, an aged cognitively unimpaired mammal, and both, to whom the compound is administered.
 32. The method according to any one of claims 25 to 31, wherein cognitive function is hippocampal-dependent function.
 33. The method according to claim 32, wherein the hippocampal-dependent function is selected from the group consisting of spatial memory acquisition, long-term spatial memory, and spatial memory retrieval.
 34. The method according to any one of claims 19 to 33, wherein the mammal is an outbred strain of rat.
 35. The method according to any one of claims 19 to 33, wherein the mammal is a human.
 36. The method according to any one of claims 19 to 24, wherein the abundance is determined in CA1, CA3 or DG hippocampal tissue.
 37. The method according to claim 1, wherein the identified gene(s) are selected from the group consisting of each of the individual genes listed in Tables 1-48.
 38. The method according to claim 2, wherein the identified gene(s) are selected from the group consisting of each of the individual genes listed in Tables 1, 2, 5, 6, 9, 10, 13, 14, 17, 18, 21, 22, 25, 26, 29, 30, 33, 34, 37, 38, 41, 42, 45 and
 46. 39. The method according to any one of claims 14, 19, 23, 26 and 30 wherein the expressed gene product is the product of the GABA-A α5 receptor α5 receptor gene (GENBANK® accession number NM_(—)017295) or its homologues. 40-42. (canceled)
 43. A pharmaceutical composition for treating cognitive impairment, the composition comprising pharmaceutically effective amount of a GABA-A α5 receptor agonist and a pharmaceutically acceptable carrier.
 44. The pharmaceutical composition according to claim 43, wherein the agonist is selected from the group consisting of 1-methyl-7-acetyleno-5-phenyl-1,3-dihydro-benzo[e]-1,4-diazepin-2-one, 6,6 dimethyl-3-(3-hydroxypropyl)thio-1-(thiazol-2-yl)-6,7-dihydro-2-benzothiophen-4(5H)-one, and 8-ethylthio-3-methyl-5-(1-oxidopyridin-2-yl)-3,4-dihydronaphthalen-1(2H)-one. 